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Conferences, Lectures, & Seminars
Events for May

  • AI Seminar-Centralities, Communities and Dynamics: The Generalized Laplacian Framework

    Fri, May 01, 2015 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Xiaoran Yan , USC/ISI

    Talk Title: Centralities, Communities and Dynamics: The Generalized Laplacian Framework

    Series: Artificial Intelligence Seminar

    Abstract: The interplay between a dynamic process and topology of a network on which it unfolds affects observed network structure. In this talk, we examine the impact of this the interaction on the identification of central nodes and communities in networks. We introduce the generalized Laplacian framework which extends the traditional Laplacian beyond simple diffusion. By mathematically relating dynamic processes to random walks on a transformed network, the generalized Laplacian formulation unifies different measures of centrality and community quality. Thus, a node's centrality describes its participation in the dynamics taking place on the network, and communities are groups of nodes that interact more frequently with each other according to the rules of the dynamic process. We prove that the classic Cheeger's inequality, which relates the spectrum of the Laplacian matrix to the conductance of the best cluster in the network, can be extended to this generalized setting, providing a method for fast graph partitioning under any dynamics. We demonstrate empirically that different dynamic processes lead to divergent views of structure of synthetic and real-world networks.






    Biography: Xiaoran Yan is a Postdoctoral Research Associate at Kristina Lerman's group at ISI-USC. His work focuses on modelling and analyzing dynamics on networks as well as the underlying topological structures. He received a Ph.D. in Computer Science at University of New Mexico.

    Host: Kristina Lerman

    Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=9e22bdf6c8be40a3a5f7abdb6c3fef251

    Location: Information Science Institute (ISI) - 11th Flr. Conf Rm # 1135, Marina Del Rey

    WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=9e22bdf6c8be40a3a5f7abdb6c3fef251d

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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  • CS Colloquium: Ari Shapiro (ICT) - Models of Motion, Movement and Interaction for Digital Characters

    Fri, May 01, 2015 @ 01:00 PM - 02:20 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Ari Shapiro, USC Institute for Creative Technologies

    Talk Title: Models of Motion, Movement and Interaction for Digital Characters

    Series: CS Colloquium

    Abstract: Research in animation has progressed where capture technologies have allowed recording and playback of human motion. For example, a human face can be recorded speaking an utterance, then accurately modeled in 3D. However, making the 3D face produce an utterance that has not previously been recorded requires an understanding of how the face reacts to the speech that is generated, how the head and neck must move to accommodate that sound as well as that expression, and how the other parts of the face and eyes act during the speech. Similarly, motion capture techniques allow the capture and replication of human walking or running as performed by the original actor, but arbitrary movement through uneven terrain with obstacles cannot be synthesized accurately, since the complexity of the human balance and structure is not accurately modeled using only kinematic points in space over time.

    Thus, while motion replication into a 3D environment is fairly well understood across a number of areas, the fundamental question of how to synthesize movement through a controllable model of humans remains elusive. The human body is extremely complex, and models of movement for high energy activities such as running differ greatly from other complex phenomena such as talking or gesturing. Thus, while it is possible to replicate a recorded motion, generating a controllable model of movement for a virtual human remains an open research problem for many different areas, ranging from facial expression to speech to gross movement. In addition, the motivations for human movement and motion are often driven by cognitive functions, so a better understanding of human movement requires a similar understanding of the cognitive aspects that motivate it.

    In this talk, I will describe my research in generating various controllable models of motion and movement for animated 3D characters. My objective is to better understand how people physically move, interact and respond to people and objects in their environment By better understanding how people move about and the motivations for doing so, we can create models of human movement and behavior that can be controlled within a virtual or digital space, thus enabling convincing virtual characters that can be used for various types of training and simulation. The embodiment of movement and behavior of a person into a controllable, digital model allows for the creation of complicated scenarios that can be effective substitutes and training environments for real-world experiences.

    The lecture will be available to stream HERE. (Right Click, New Tab for optimal results.)

    Biography: Ari Shapiro currently works as a Research Scientist at the USC Institute for Creative Technologies, where his focus is on synthesizing realistic animation for virtual characters as lead of the Character Animation and Simulation research group. Shapiro has published many academic articles in the field of computer graphics and animation for virtual characters, and is a seven-time SIGGRAPH speaker.
    For several years, he worked on character animation tools and algorithms in the research and development departments of visual effects and video games companies such as Industrial Light and Magic, LucasArts and Rhythm and Hues Studios. He has worked on many feature-length films, and holds film credits in The Incredible Hulk and Alvin and the Chipmunks 2. In addition, he holds video games credits in the Star Wars: The Force Unleashed series.
    He completed his Ph.D. in computer science at UCLA in 2007 in the field of computer graphics with a dissertation on character animation using motion capture, physics and machine learning. He also holds an M.S. in computer science from UCLA, and a B.A. in computer science from the University of California, Santa Cruz.


    Host: CS Department

    Webcast: https://bluejeans.com/57723254

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 108

    WebCast Link: https://bluejeans.com/577232541

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Astani Civil and Environmental Engineering Ph.D. Seminar

    Fri, May 01, 2015 @ 03:00 PM - 04:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Mahsa Moslehi and Charanraj Thimmisetty, Astani CEE Ph.D. Candidates

    Talk Title: TBA

    Abstract: TBA

    Location: Seeley G. Mudd Building (SGM) - 101

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

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  • CS Colloquium: Wei Cheng (UCLA) - Integrating Multiple Networks for Big Data Analysis

    Tue, May 05, 2015 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Wei Cheng, UCLA

    Talk Title: Integrating Multiple Networks for Big Data Analysis

    Series: CS Colloquium

    Abstract: In many big data applications, data with complex structures can usually be modeled as network data. Usually, for one data mining problem, we have multiple networks. For one thing, data about the same object can be obtained from various. For another, the different objects may have complex structures and can be interrelated in a complex way. Integration of different network data is valuable for reaching a more accurate decision and discovering novel patterns. The task is challenging because of the inherent characteristics of the networks: 1) variety (e.g., complex structures, heterogeneous types and data sources); and 2) poor quality; 3) massive volume. In this talk, I will present our research efforts to use big data technologies to integrate multiple networks for both supervised and unsupervised data mining problems. First, I will begin by presenting the work of integrative analyzing multi-domain heterogeneous data for graph clustering. Next, I will present the work on robust sparse regression algorithm that integrates multi-source heterogeneous networks.

    Biography: Wei Cheng is a Ph.D. candidate in Computer Science at University of North Carolina at Chapel Hill. He has been visiting Department of Computer Science of UCLA since 2013. He received a Master's and Bachelor's degree from Tsinghua University and Nanjing University, in 2010 and 2006, respectively. His research interests include big data, data mining, bioinformatics, computational biology, and machine learning. He is especially interested in scalable data analysis problems for data science with an emphasis on biological applications Previously, he also conducted research at Microsoft Research and IBM Research as an intern.

    Host: Yan Liu

    Location: Henry Salvatori Computer Science Center (SAL) - 213

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • EE Pioneer Series - Jerry M. Mendel

    Tue, May 05, 2015 @ 02:00 PM - 04:00 PM

    Ming Hsieh Department of Electrical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Jerry Mendel, Professor of Electrical Engineering

    Talk Title: Ode to Joy of Research

    Series: Pioneer Series

    Abstract: To me Research is synonymous with Exploration, traveling into the great unknown and hopefully discovering something that no one else has seen before. Just as Explorers must ask critical questions, many of which are open-ended, in what we call “Research” it’s important, arguably crucially important, to focus on asking the right questions. In this short talk I’m going to focus on some of the questions that I’ve asked or that my students have asked so you get a very good sense of what I mean, beginning with my days as a graduate student, continuing with my years in industry and concluding with my more than 40 years at USC. I have been very fortunate to have experienced the joy of research for more than 50 years, and will also highlight especially joyous moments.

    Biography: Jerry M. Mendel received the Ph.D. degree in electrical engineering from the Polytechnic Institute of Brooklyn, Brooklyn, NY. Currently he is Professor of Electrical Engineering at USC, where he has been since 1974. He has published over 550 technical papers and is author and/or co-author of 12 books. His present research interests include: type-2 fuzzy logic systems and their applications to a wide range of problems, including smart oil field technology, computing with words, and fuzzy set qualitative comparative analysis. He is a Life Fellow of the IEEE, a Distinguished Member of the IEEE Control Systems Society, and a Fellow of the International Fuzzy Systems Association. He was President of the IEEE Control Systems Society in 1986. He was a member of the Administrative Committee of the IEEE Computational Intelligence Society for nine years, and was Chairman of its Fuzzy Systems Technical Committee and the Computing With Words Task Force of that TC. Among his awards are the 1983 Best Transactions Paper Award of the IEEE Geoscience and Remote Sensing Society, the 1992 Signal Processing Society Paper Award, the 2002 and 2014 Transactions on Fuzzy Systems Outstanding Paper Awards, a 1984 IEEE Centennial Medal, an IEEE Third Millenium Medal, and a Fuzzy Systems Pioneer Award (2008) from the IEEE Computational Intelligence Society.

    Host: Ming Hsieh Institute

    More Info: http://mhi.usc.edu/about/news/2015/04/20/ee-pioneer-series-jerry-m-mendel/

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Elise Herrera-Green

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  • CS Colloquium: Kate Saenko (University of Massachusetts Lowell) - From Video to Sentences: A Deep Learning Approach

    Wed, May 06, 2015 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Kate Saenko , University of Massachusetts Lowell

    Talk Title: From Video to Sentences: A Deep Learning Approach

    Series: CS Colloquium

    Abstract: I will describe several recent advances in automatic generation of natural language descriptions for video. Video description has important applications in human-robot interaction, video indexing, and describing movies for the blind. Real-world videos often have complex dynamics, but current methods are insensitive to temporal structure and do not allow both input (sequence of frames) and output (sequence of words) of variable length. I will describe a novel sequence-to-sequence neural network that learns to generate captions for brief videos. The model is trained on video-sentence pairs and is naturally able to learn the temporal structure of the sequence of frames as well as the sequence model of the generated sentences, i.e. a language model. To further handle the ambiguity over multiple objects and locations, the model incorporates convolutional networks with Multiple Instance Learning (MIL) to consider objects in different positions and at different scales simultaneously. The multi-scale multi-instance convolutional network is integrated with a sequence-to-sequence recurrent neural network to generate sentence descriptions based on the visual representation. This architecture is the first end-to-end trainable deep neural network that is capable of multi-scale region processing for video description. I will show results of captioning YouTube videos and Hollywood movies.

    Biography: Kate Saenko is an Assistant Professor of Computer Science at the University of Massachusetts Lowell. She received her PhD from MIT, followed by postdoctoral work at UC Berkeley and Harvard. Her research spans the areas of computer vision, machine learning, speech recognition, and human-robot interfaces. Dr Saenko's current research interests include domain adaptation for object recognition and joint modeling of language and vision. She is involved in a large multi-institution NSF-sponsored project, conducting research in statistical scene understanding and physics-based visual reasoning. She is also a recipient of an NSF EAGER award to analyse domain invariance of deep learning models. Previously, she was involved in DARPA's Mind's Eye project, developing methods for recognizing and describing human activities in video.

    Host: Fei Sha

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 222

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Learning Longer Memory in Recurrent Networks

    Tue, May 12, 2015 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Tomas Mikolov , Research Scientist at Facebook AI Reseach

    Talk Title: Learning Longer Memory in Recurrent Networks

    Series: AISeminar

    Abstract: Recurrent neural network is a powerful model that learns temporal patterns in sequential data. For a long time, it was believed that recurrent networks are difficult to train using simple optimizers, such as stochastic gradient descent, due to the so-called vanishing gradient problem. In this talk, I will show that learning longer term patterns in real data, such as in natural language, is perfectly possible using gradient descent. This is achieved by using a slight structural modification of the simple recurrent neural network architecture. Some of the hidden units are encouraged to change their state slowly by constraining part of the recurrent weight matrix to be close to identity, thus forming kind of a longer term memory. We evaluate our model in language modeling experiments, where we obtain similar performance to the much more complex Long Short Term Memory (LSTM) networks. This is a joint work with Armand Joulin, Sumit Chopra, Michael Mathieu and Marc'Aurelio Ranzato.

    Biography: Tomas Mikolov is a research scientist at Facebook AI Research. His work includes introduction of recurrent neural networks to statistical language modeling (published as open-source RNNLM toolkit), and an efficient algorithm for estimating word representations in continuous space (the Word2vec project). His current interest is in developing techniques and datasets that would help to advance research towards artificial intelligence systems capable of natural communication with people.

    Website: https://research.facebook.com/researchers/643234929129233/tomas-mikolov/


    Host: Ashish Vaswani

    Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=19140806ae5e4116ab2644b1c1d86bbe1

    Location: Information Science Institute (ISI) - 1135

    WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=19140806ae5e4116ab2644b1c1d86bbe1d

    Audiences: Everyone Is Invited

    Posted By: Alma Nava / Information Sciences Institute

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  • Teamcore Seminar: Dr. William Haskell (National University of Singapore) - Approximate Dynamic Programming

    Wed, May 13, 2015 @ 10:30 AM - 11:30 AM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. William Haskell, National University of Singapore

    Talk Title: Approximate Dynamic Programming

    Series: Teamcore Seminar

    Abstract: We develop a new technique for analyzing the convergence of stochastic algorithms. This technique is based on the notion of stochastic dominance and allows us to get sample complexity results. We apply this technique to study the convergence of several approximate dynamic programming algorithms for MDPs on continuous state spaces, as well as to propose some new algorithms.

    Biography: Dr. William Haskell is an assistant professor in the department of the industrial & systems engineering at National University of Singapore. He obtained a PhD from the department of industrial engineering and operation research from UC Berkeley. He was a visiting scholar at USC ISE department from August 2011 to May 2013 and then a Postdoctoral Research Associate from June 2011 to May 2014 at the USC EE and CS department. His research has focused on risk-aware decision making, sequential and large-scale optimization and data-driven decision making.

    Host: Teamcore Research Group

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • AI Seminar: Computerized Search for Causal Relations in High Dimensional Data: Some Results and Many Problems

    Wed, May 13, 2015 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Clark Glymour , Alumni University Professor, Carnegie Mellon University

    Talk Title: Computerized Search for Causal Relations in High Dimensional Data: Some Results and Many Problems

    Series: Artificial Intelligence Seminar

    Abstract: I will briefly review the graphical causal model framework and describe some of the search strategies that have proved practical in small dimensional problems. Then I will describe some of the modifications we have recently pursued at Carnegie Mellon to allow search in high dimensional problems, e.g, 50.000 - 1,000,000 variables, with sample sizes orders of magnitude smaller, and some of the many problems we have not satisfactorily solved.

    Biography: Clark Glymour is the Alumni University Professor in the Department of Philosophy at Carnegie Mellon University. He is also a senior research scientist at the Florida Institute for Human and Machine Cognition. He is the founder of the Philosophy Department at Carnegie Mellon University, a Guggenheim Fellow, a Fellow of the Center for Advanced Study in Behavioral Sciences a Phi Beta Kappa lecturer, and is a Fellow of the statistics section of the AAAS. Glymour and his collaborators created the causal interpretation of Bayes nets and developed an automated causal inference algorithm implemented as software named TETRAD. His areas of interest include epistemology (particularly Android epistemology), machine learning, automated reasoning, psychology of judgment, and mathematical psychology.

    Host: Kun Zhang

    More Info: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=ebaa5ed5e1444cbfa7aea272f321509d1d
    Webcast: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=ebaa5ed5e1444cbfa7aea272f321509d1

    Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey

    WebCast Link: http://webcasterms1.isi.edu/mediasite/Viewer/?peid=ebaa5ed5e1444cbfa7aea272f321509d1d

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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  • Communications, Networks & Systems (CommNetS) Seminar

    Wed, May 13, 2015 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Frank C. Langbein, Cardiff University

    Talk Title: Controlling Information Transfer in Spintronics Networks

    Series: CommNetS

    Abstract: The propagation of information encoded in spin degrees of freedom through networks of coupled spins enables important applications in spintronics and quantum information processing. Control is required to direct the flow of information through a spintronic network in an efficient manner, e.g for an on-chip interconnect or for routing quantum information. In principle information stored in spin states can propagate through a network of coupled spins without any charge transport. As propagation of spin-based information is governed by quantum-mechanics and the Schrodinger equation, excitations in a spin network propagate, disperse and refocus in a wave-like manner. We study control of information propagation in rings of spins as a simple prototype of a router for spin-based information. For our purposes we restrict ourselves to spin-1/2 particles with uniform nearest neighbour couplings forming a ring with a single excitation (or one bit) in the network. Control can be utilised to maximise transfer efficiency and speed of this excitation. We specifically consider optimising spatially distributed potentials, which remain constant during the evolution, in contrast to dynamic control schemes, which require dynamic modulation or fast switching of the control potentials. Due to the limited degrees of freedom in the system, finding a control that maximises the transfer probability in a short time is difficult, but in principle simplifies the implementation of the routing scheme. For practical implementation of such a scheme specific network structures and spin coupling strengths will have to be identified from measurements of actual devices to build a model suitable to find the necessary controls. For this we present an approach for discriminating between different network structures and learning model parameters.

    Biography: Frank C Langbein is a lecturer in computer science at Cardiff University, leading the Quantum Technologies Group, and is a member of the Geometric Computing and Computer Vision research group. He is also a member of the Research Institute for Visual Computing where he is co-leading the sub-programme on vision-based geometric modelling and the interface with science. He received a diploma in mathematics from Stuttgart University in 1998 and a PhD from Cardiff University in 2003.
    He is working on computational and geometric modelling, control, machine learning and visual computing with applications in quantum technologies, healthcare, mechanical and chemical engineering and spintronics.

    Host: Prof. Edmond Jonckheere

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Posted By: Annie Yu

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  • NL Seminar- Exploring LDA: Parallel Inference and Model Selection

    Fri, May 15, 2015 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Dehua Cheng, (USC/Melady)

    Talk Title: Exploring LDA: Parallel Inference and Model Selection

    Series: Natural Language Seminar

    Abstract: Latent Dirichlet allocation (LDA) and its Bayesian nonparametric generalization hierarchical Dirichlet processes (HDP) have been proven successful in modeling large, complex, real-world domains. However, inference on LDA/HDP is challenging and it has received notable attention from the researchers. In this talk, we present two algorithmic advances for LDA/HDP inference by examining their mathematical properties. We will first present an effective parallel Gibbs sampling algorithm for LDA/HDP by exploring the equivalency between the Dirichlet-multinomial hierarchy and the Gamma-Poisson hierarchy. Secondly, we will show how to provably select the number of topics for LDA by studying the spectral space of its second order moments (bi-gram statistics).


    Biography: Dehua Cheng is a third year Ph.D. student in the CS department at USC, advised by Professor Yan Liu. Prior to that, he received his B.S. degree in Mathematics and Physics from Tsinghua University, China. His research interests include randomized numerical algorithm in machine learning and parallel inference for probabilistic graphical model.

    Host: Nima Pourdamghani and Kevin Knight

    More Info: http://nlg.isi.edu/nl-seminar/

    Location: Information Science Institute (ISI) - 6th Flr Conf Rm # 689, Marina Del Rey

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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  • Repeating EventShort Course: Six Sigma Green Belt for Process Improvement

    Tue, May 19, 2015

    Distance Education Network

    Conferences, Lectures, & Seminars


    Abstract: This program, an introductory course in Six Sigma, will give you a thorough understanding of Six Sigma and its focus on eliminating defects through fundamental process knowledge. Topics covered in addition to DMAIIC and Six Sigma philosophy include basic statistics, statistical process control, process capability, financial implications and root cause analysis.

    This program is offered both in the classroom and online.

    Register Now!

    Audiences: Registered Attendees

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    Posted By: Viterbi Professional Programs

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  • Compressive Sensing RF Signals with Photonic Systems

    Tue, May 19, 2015 @ 10:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. George Valley, Aerospace Corporation

    Talk Title: Compressive Sensing RF Signals with Photonic Systems

    Abstract: We and other researchers worldwide have now developed several photonics approaches for measuring the properties of sparse RF signals using compressive sensing. In this talk I will review the most promising of these approaches, compare them and talk about several special issues that arise in photonic compressive sensing. These issues include mixing matrix calibration, recovery of off-the-grid sinusoids, and reducing system complexity.

    Biography: George C. Valley has an AB from Dartmouth College and a PhD from The University of Chicago, both in physics. He has worked at Cornell Aeronautical Laboratories, Hughes Aircraft Company, and is now Senior Scientist at The Aerospace Corporation. Past research work has focused on nonlinear optics, optical solitons, photorefractive materials, free-space laser communication and wave propagation in random media. Current research interests include photonic analog-to-digital converters, optical signal processing and compressive sensing.

    Host: Urbashi Mitra, ubli@usc.edu, EEB 536, x04667

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 539

    Audiences: Everyone Is Invited

    Posted By: Gerrielyn Ramos

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  • Artificial vs AuthenticThe Art of Language Invention

    Tue, May 19, 2015 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: David Peterson , HBOs Game of Thrones

    Talk Title: Artificial vs Authentic:The Art of Language Invention

    Series: Artificial Intelligence Seminar

    Abstract: As long as humans have been using language, humans have been inventing language. Linguistic creativity has taken many different forms over the years, but it's made its greatest strides in the past 25 years. For languages like Esperanto and Volapük, functionality and unambiguity were lofty design goals. Today, with languages created for entirely different purposes, functionality is considered a prerequisite, and unambiguity a major design flaw. In this talk, David Peterson discusses naturalistic language creation, and the emerging art form known as conlanging.

    Biography: David Peterson is a language creator and author. Since 2009, he's been working on HBO's Game of Thrones, having created the Dothraki and Valyrian languages. Since then, he's gone on to work on a number of other projects, including Syfy's Defiance, Syfy's Dominion, Marvel's Thor: The Dark World, the CW's Star-Crossed, the CW's The 100, and Showtime's Penny Dreadful. He authored the book Living Language Dothraki, an introductory guide to the Dothraki language, and in September, he'll be publishing The Art of Language Invention with Penguin Random House.

    Host: Ashish Vaswani

    More Info: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=714b19be3e114ca79ddb3ccfb55366f01d
    Webcast: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=714b19be3e114ca79ddb3ccfb55366f01

    Location: Information Science Institute (ISI) - 11th Flr Conf Rm s1135 & 1137 Marina Del Rey

    WebCast Link: http://webcasterms1.isi.edu/mediasite/SilverlightPlayer/Default.aspx?peid=714b19be3e114ca79ddb3ccfb55366f01d

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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  • Repeating EventShort Course: Six Sigma Green Belt for Process Improvement

    Wed, May 20, 2015

    Distance Education Network

    Conferences, Lectures, & Seminars


    Abstract: This program, an introductory course in Six Sigma, will give you a thorough understanding of Six Sigma and its focus on eliminating defects through fundamental process knowledge. Topics covered in addition to DMAIIC and Six Sigma philosophy include basic statistics, statistical process control, process capability, financial implications and root cause analysis.

    This program is offered both in the classroom and online.

    Register Now!

    Audiences: Registered Attendees

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    Posted By: Viterbi Professional Programs

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  • Repeating EventShort Course: Six Sigma Green Belt for Process Improvement

    Thu, May 21, 2015

    Distance Education Network

    Conferences, Lectures, & Seminars


    Abstract: This program, an introductory course in Six Sigma, will give you a thorough understanding of Six Sigma and its focus on eliminating defects through fundamental process knowledge. Topics covered in addition to DMAIIC and Six Sigma philosophy include basic statistics, statistical process control, process capability, financial implications and root cause analysis.

    This program is offered both in the classroom and online.

    Register Now!

    Audiences: Registered Attendees

    View All Dates

    Posted By: Viterbi Professional Programs

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  • NL Seminar- How to Memorize a Random 60-Bit String

    Fri, May 22, 2015 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Marjan Ghazvininejad, USC/ISI

    Talk Title: How to Memorize a Random 60-Bit String

    Series: Natural Language Seminar

    Abstract: User-generated passwords tend to be memorable, but not secure. A random, computer-generated 60-bit string is much more secure. However, users cannot memorize random 60-bit strings. In this paper, we investigate methods for converting arbitrary bit strings into English word sequences (both prose and poetry), and we study their memorability and other properties.



    Biography: Marjan Ghazvininejad is a second year PhD student in Computer Science at University of Southern California (USC). She is working with Professor Kevin Knight at the Information Sciences Institute (ISI). She is interested in natural language processing, especially the application of machine learning techniques in this area.

    Host: Nima Pourdamghani and Kevin Knight

    More Info: http://nlg.isi.edu/nl-seminar/

    Location: Information Science Institute (ISI) - 6th Flr Conf Rm # 689, Marina Del Rey

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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  • CS Colloquium: Jelena Marašević (Columbia U.) - Full-Duplex Wireless: Resource Allocation and Rate Gains for Realistic Hardware Models

    Tue, May 26, 2015 @ 10:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jelena Marašević, Columbia University

    Talk Title: Full-Duplex Wireless: Resource Allocation and Rate Gains for Realistic Hardware Models

    Series: CS Colloquium

    Abstract: Full-duplex communication -“ simultaneous transmission and reception on the same frequency channel -- has the potential to substantially increase the throughput in wireless networks. The achievable rate gains and the effect of full-duplex capabilities on physical and medium access control (MAC) layers, however, are still not fully understood. In this talk, I will present our recent results on power allocation in single-channel and multi-channel settings, where the objective is to maximize the sum of the rates on uplink and downlink full-duplex channels. Specifically, I will discuss power allocation in the single-channel use cases, and present a sufficient condition under which the sum of uplink and downlink rates on a full-duplex channel is concave in the transmission power levels. This condition is essential for the design of a power allocation algorithm in the multi-channel setting. For the multi-channel setting, I will present a new realistic model of a small form-factor (e.g., a smartphone) full-duplex receiver, demonstrating its accuracy via measurement results. For the problem of jointly allocating power levels to different channels, where the objective is maximizing the sum of the rates over uplink and downlink OFDM channels, I will present two algorithms. The first is a polynomial-time algorithm that is nearly optimal under very mild restrictions. The second algorithm reduces the running time substantially, and is nearly-optimal under the high SINR approximation. Overall, our results provide a precise quantification of the achievable rate gains as a function of signal-to-noise ratios and (self-)interference-to-noise-ratios.

    Based on joint work with J. Zhou, H. Krishnaswamy, Y. Zhong, and G. Zussman that will appear in Proc. ACM SIGMETRICS '15.

    Biography: Jelena Marašević is a Ph.D. student at Columbia University. Her research focuses on algorithms for fair resource allocation problems, with applications in wireless networks. She received her B.Sc. degree from University of Belgrade, School of Electrical Engineering, in 2011, and her M.S. degree in electrical engineering from Columbia University in 2012. Jelena is a recipient of the M.S. Award of Excellence and the Jacob Millman Prize for Excellence in Teaching Assistance from Columbia University. She is also a winner of the Qualcomm Innovation Fellowship 2015 award.

    Host: CS Department

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • CS Colloquium: Jelena Marasevic (Columbia U.) - Full-Duplex Wireless: Resource Allocation and Rate Gains for Realistic Hardware Models

    Tue, May 26, 2015 @ 10:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Jelena Marasevic, Columbia University

    Talk Title: Full-Duplex Wireless: Resource Allocation and Rate Gains for Realistic Hardware Models

    Series: CS Colloquium

    Abstract: Full-duplex communication -“ simultaneous transmission and reception on the same frequency channel -- has the potential to substantially increase the throughput in wireless networks. The achievable rate gains and the effect of full-duplex capabilities on physical and medium access control (MAC) layers, however, are still not fully understood. In this talk, I will present our recent results on power allocation in single-channel and multi-channel settings, where the objective is to maximize the sum of the rates on uplink and downlink full-duplex channels. Specifically, I will discuss power allocation in the single-channel use cases, and present a sufficient condition under which the sum of uplink and downlink rates on a full-duplex channel is concave in the transmission power levels. This condition is essential for the design of a power allocation algorithm in the multi-channel setting. For the multi-channel setting, I will present a new realistic model of a small form-factor (e.g., a smartphone) full-duplex receiver, demonstrating its accuracy via measurement results. For the problem of jointly allocating power levels to different channels, where the objective is maximizing the sum of the rates over uplink and downlink OFDM channels, I will present two algorithms. The first is a polynomial-time algorithm that is nearly optimal under very mild restrictions. The second algorithm reduces the running time substantially, and is nearly-optimal under the high SINR approximation. Overall, our results provide a precise quantification of the achievable rate gains as a function of signal-to-noise ratios and (self-)interference-to-noise-ratios.

    Based on joint work with J. Zhou, H. Krishnaswamy, Y. Zhong, and G. Zussman that will appear in Proc. ACM SIGMETRICS '15.

    Biography: Jelena Marasevic is a Ph.D. student at Columbia University. Her research focuses on algorithms for fair resource allocation problems, with applications in wireless networks. She received her B.Sc. degree from University of Belgrade, School of Electrical Engineering, in 2011, and her M.S. degree in electrical engineering from Columbia University in 2012. Jelena is a recipient of the M.S. Award of Excellence and the Jacob Millman Prize for Excellence in Teaching Assistance from Columbia University. She is also a winner of the Qualcomm Innovation Fellowship 2015 award.

    Host: CS Department

    Location: 248

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Repeating EventShort Course: Lean Green Belt

    Wed, May 27, 2015

    Distance Education Network

    Conferences, Lectures, & Seminars


    Abstract: This three-day course provides an in-depth understanding of lean enterprise principles and how to apply them within your organization. Your lean journey begins with a series of interactive simulations that demonstrate how each lean concept is applied and its impact on the process. Mapping the process flow and identifying the activities that add value from the customer's perspective is the cornerstone of this class. The class is then given a scenario and the students simulate the conversion from traditional to lean in a practical hands-on environment. The course also provides a structure for how to manage a lean process for continuous improvement. Participants will learn how to structure their organizations to support and continuously improve a lean process. Participants will also fully understand how to implement 5S within their plants and how to begin reducing setup time using the SMED process.



    More Info: http://gapp.usc.edu/professional-programs/short-courses/industrial-systems/lean-green-belt

    Audiences: Registered Attendees

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    Posted By: Viterbi Professional Programs

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  • Repeating EventShort Course: Lean Green Belt

    Thu, May 28, 2015

    Distance Education Network

    Conferences, Lectures, & Seminars


    Abstract: This three-day course provides an in-depth understanding of lean enterprise principles and how to apply them within your organization. Your lean journey begins with a series of interactive simulations that demonstrate how each lean concept is applied and its impact on the process. Mapping the process flow and identifying the activities that add value from the customer's perspective is the cornerstone of this class. The class is then given a scenario and the students simulate the conversion from traditional to lean in a practical hands-on environment. The course also provides a structure for how to manage a lean process for continuous improvement. Participants will learn how to structure their organizations to support and continuously improve a lean process. Participants will also fully understand how to implement 5S within their plants and how to begin reducing setup time using the SMED process.



    More Info: http://gapp.usc.edu/professional-programs/short-courses/industrial-systems/lean-green-belt

    Audiences: Registered Attendees

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    Posted By: Viterbi Professional Programs

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  • CS Colloquium: Hyun Soo Park (University of Pennsylvania) - Computational Social Cognition

    Thu, May 28, 2015 @ 12:00 PM - 01:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Hyun Soo Park, University of Pennsylvania

    Talk Title: Computational Social Cognition

    Series: CS Colloquium

    Abstract: Humans interact with one another by sending visible social signals such as facial expressions, body gestures, and gaze directions.

    Computational understanding of these social signals is becoming more important for artificial agents such as service robots because they are increasingly integrated in our social space.

    In this talk, I will present a computational framework for social cognition - the ability to perceive, model, and predict social signals.

    The main challenges of developing computational social cognition are that 1) social signals are too subtle to be detected by current computer vision solutions and 2) they cannot be understood by analyzing an individual signal in isolation as they are reliant upon each other. I will argue that first person cameras, e.g., head-mounted cameras, are an ideal sensor placement to capture such subtlety and will show that the relationship between the signals can be modeled by leveraging a 3D reconstruction of human body motion. In the first part of my talk, I will focus on joint attention that encodes the relationship between gaze directions and present its predictive model to recognize social interactions. This predictive model is applied various tasks, e.g., event video editing, social anomaly recognition, and region of interest detection. In the second part, I will introduce a large scale motion capture system (510 cameras) to recover subtle social signals. This system reconstructs dense 3D trajectories of body gestures at unprecedented level of high spatial resolution (~20,000 trajectories per body). Then, I will demonstrate applications of computational social cognition in behavioral analysis, sport analytics, and robotics.

    Biography: Hyun Soo Park is a Postdoctoral Fellow in Computer and Information Science at the University of Pennsylvania working with Prof. Jianbo Shi. He earned Ph.D. degree from Carnegie Mellon University in 2014 under the supervision of Prof. Yaser Sheikh. His research aims to develop a computational representation of social behaviors. He has over 15 publications in top tier conferences and journals that include computer vision (IJCV, ICCV, CVPR, ECCV), graphics (SIGGRAPH), machine learning (NIPS), and robotics (IJRR, ICRA, IROS). He organized Workshop on Human Behavior Understanding (2014) in conjunction with ECCV 2014 and will give a tutorial on Group Behavioral Analysis and its Applications in conjunction with CVPR 2015 based on his Ph.D. thesis. His work has been covered by various major media including Discovery Channel, MSNBC, WIRED, NSF, and Slashdot. Prior to his Ph.D., he received his M.S. degree from Carnegie Mellon University and his B.S. degree from POSTECH.

    Host: Hao Li

    Location: Henry Salvatori Computer Science Center (SAL) - 322

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • Repeating EventShort Course: Lean Green Belt

    Fri, May 29, 2015

    Distance Education Network

    Conferences, Lectures, & Seminars


    Abstract: This three-day course provides an in-depth understanding of lean enterprise principles and how to apply them within your organization. Your lean journey begins with a series of interactive simulations that demonstrate how each lean concept is applied and its impact on the process. Mapping the process flow and identifying the activities that add value from the customer's perspective is the cornerstone of this class. The class is then given a scenario and the students simulate the conversion from traditional to lean in a practical hands-on environment. The course also provides a structure for how to manage a lean process for continuous improvement. Participants will learn how to structure their organizations to support and continuously improve a lean process. Participants will also fully understand how to implement 5S within their plants and how to begin reducing setup time using the SMED process.



    More Info: http://gapp.usc.edu/professional-programs/short-courses/industrial-systems/lean-green-belt

    Audiences: Registered Attendees

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    Posted By: Viterbi Professional Programs

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  • CS Colloquium: Baoquan Chen (Shandong University) - 3D Urban Sensing and Visualization

    Fri, May 29, 2015 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Baoquan Chen, Shandong University

    Talk Title: 3D Urban Sensing and Visualization

    Series: CS Colloquium

    Abstract: 3D modeling of urban environments starts to play an increasingly important role in the emerging technologies from self-driving car to augmented reality. Beyond helping a human or a vehicle navigate, 3D urban models provide a base for spatially registering otherwise chaotic urban data, both sensor sensed and user generated, for better 'mapping' of urban big data. In this talk, I will introduce our decade long effort on acquiring and modeling large urban environments as well as analyzing and visualizing urban activities. I will also discuss future developments in this direction.

    Biography: Baoquan Chen is a Professor and Dean (CS & Software) of Shandong University. Prior to the current post, he was the founding director of the Visual Computer Research Center, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences, and a faculty member at CS&E at the University of Minnesota at Twin Cities. His research interests generally lie in computer graphics, visualization, and human-computer interaction. Chen received PhD in CS from SUNY@Stony Brook, and MS in EE from Tsinghua. He received NSF CAREER award in 2003 and IEEE Visualization Best Paper Award in 2005. Chen served as conference chair of IEEE Visualization 2005, and more recently SIGGRAPH Asia 2014. More at: http://www.cs.sdu.edu.cn/ baoquan/

    Host: Hao Li

    Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 101

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

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  • NL Seminar-How to Make a Frenemy: Multitape FSTs for Portmanteau Generation

    Fri, May 29, 2015 @ 03:00 PM - 04:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Aliya Deri, USC/ISI

    Talk Title: How to Make a Frenemy: Multitape FSTs for Portmanteau Generation

    Abstract: A portmanteau is a type of compound word that fuses the sounds and meanings of two component words; for example, "frenemy" (friend + enemy) or smog (smoke + fog). We develop a system, including a novel multitape FST, that takes an input of two words and outputs possible portmanteaux. Our system is trained on a list of known portmanteaux and their component words, and achieves 45% exact matches in cross-validated experiments.

    Biography: Aliya Deri is a PhD candidate at USC/ISI.




    Host: Nima Pourdamghani and Kevin Knight

    More Info: http://nlg.isi.edu/nl-seminar/

    Location: 6th Flr Conf Rm # 689, Marina Del Rey

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

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