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Conferences, Lectures, & Seminars
Events for August
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Six Sigma Black BeltMon, Aug 05, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: Week 1: June 4-7, 2019
Week 2: July 15-19, 2019
Week 3: August 5-9, 2019
9am - 5pm
Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of Six Sigma to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certificate. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
NOTE: Participants must provide a windows based computer running Microsoft Office to the seminar.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Posted By: Corporate & Professional Programs
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MHI Medical Imaging Seminar
Mon, Aug 05, 2019 @ 12:00 PM - 01:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Wayne Chen, Electrical & Computer Engineering, University of Southern California
Talk Title: Functional Real-time MRI of the Upper Airway
Series: Medical Imaging Seminar Series
Abstract: MRI is arguably the most promising imaging modality for evaluating upper airway dynamics as it is non-invasive and involves no ionizing radiation. For the past decade, real-time MRI has been extensively used with significant improvement on the spatiotemporal resolution to time-resolve the dynamics of the upper airway during natural speech production and sleep. Existing techniques focus on tracking tissue surfaces, such as vocal track shaping and airway cross-section contour. However, they lack the ability to measure the function of the upper airway, such as the internal muscle movement and the physiological variation across different airway sites.
This talk will introduce new techniques and novel experiment design compatible with real-time MRI techniques in order to reveal the internal muscle motion and physiological traits of the upper airway. We leverage the maturing fast scan methods to provide adequate spatiotemporal resolution, while propose novel techniques and experiment design to go beyond fast. With the proposed methods, we can set our eyes further than the anatomical structures and onto the even more interesting yet intrinsically complex functions of the upper airway.
Biography: Wayne Chen is a Ph.D. candidate working under the supervision of Prof. Krishna Nayak at the Magnetic Resonance Engineering Laboratory. His research focuses on MR pulse sequence development and reconstruction for real-time imaging of the upper airway.
Host: Professor Krishna Nayak
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Talyia White
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Six Sigma Black Belt
Tue, Aug 06, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: Week 1: June 4-7, 2019
Week 2: July 15-19, 2019
Week 3: August 5-9, 2019
9am - 5pm
Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of Six Sigma to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certificate. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
NOTE: Participants must provide a windows based computer running Microsoft Office to the seminar.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Posted By: Corporate & Professional Programs
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Six Sigma Black Belt
Wed, Aug 07, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: Week 1: June 4-7, 2019
Week 2: July 15-19, 2019
Week 3: August 5-9, 2019
9am - 5pm
Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of Six Sigma to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certificate. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
NOTE: Participants must provide a windows based computer running Microsoft Office to the seminar.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Posted By: Corporate & Professional Programs
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Six Sigma Black Belt
Thu, Aug 08, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: Week 1: June 4-7, 2019
Week 2: July 15-19, 2019
Week 3: August 5-9, 2019
9am - 5pm
Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of Six Sigma to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certificate. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
NOTE: Participants must provide a windows based computer running Microsoft Office to the seminar.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Posted By: Corporate & Professional Programs
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NL Seminar-MODELLING THE INTERPLAY OF METAPHOR AND EMOTION, AND A PEEK AT THE UNDERLYING COGNITIVE MECHANISMS
Thu, Aug 08, 2019 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Ekaterina Shutova, Univ of Amsterdan
Talk Title: MODELLING THE INTERPLAY OF METAPHOR AND EMOTION, AND A PEEK AT THE UNDERLYING COGNITIVE MECHANISMS
Series: Natural Language Seminar
Abstract: Besides making our thoughts more vivid and filling our communication with richer imagery, metaphor plays a fundamental structural role in our cognition, helping us to organise and project knowledge. For example, when we say "a well-oiled political machine", we view the concept of political system in terms of a mechanism and transfer inferences from the domain of mechanisms onto our reasoning about political processes. Much previous research on metaphor in linguistics and psychology suggests that metaphorical phrases tend to be more emotionally evocative than their literal counterparts. In this talk, I will present our recent work investigating the relationship between metaphor and emotion within a computational framework, by proposing the first joint model of these phenomena. We experiment with several multitask learning architectures for this purpose and demonstrate that metaphor identification and emotion prediction mutually benefit from joint learning, advancing the state of the art in both of these tasks.
In the second half of the talk, I will discuss how general-purpose semantic representations can be used to better understand metaphor processing in the human brain. In a series of experiments, we evaluate a range of semantic models word embeddings, compositional models, visual and multimodal models in their ability to decode brain activity associated with reading of literal and metaphoric sentences. Our results point to interesting differences in the processing of metaphorical and literal language.
Biography: Ekaterina Shutova is an Assistant Professor at the Institute for Logic, Language and Computation at the University of Amsterdam. Her research is in the area of natural language processing with a specific focus on computational semantics, figurative language processing, multilingual NLP and cognitively driven semantics. Previously, she worked at the University of Cambridge Computer Laboratory and the International Computer Science Institute and the Institute for Cognitive and Brain Sciences at the University of California, Berkeley. She received her PhD in Computer Science from the University of Cambridge in 2011.
Host: Xusen Yin
More Info: https://nlg.isi.edu/nl-seminar
Webcast: https://bluejeans.com/s/Mws0S/Location: Information Science Institute (ISI) - CR #1014-Multi Purpose Rm
WebCast Link: https://bluejeans.com/s/Mws0S/
Audiences: Everyone Is Invited
Posted By: Peter Zamar
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Six Sigma Black Belt
Fri, Aug 09, 2019 @ 09:00 AM - 05:00 PM
Executive Education
Conferences, Lectures, & Seminars
Abstract: Week 1: June 4-7, 2019
Week 2: July 15-19, 2019
Week 3: August 5-9, 2019
9am - 5pm
Learn the advanced problem-solving skills you need to implement the principles, practices, and techniques of Six Sigma to maximize performance and cost reductions in your organization. During this three-week practitioner course, you will learn how to measure a process, analyze the results, develop process improvements, and quantify the resulting savings. You will be required to complete a project demonstrating mastery of appropriate analytical methods and pass an examination to earn Six Sigma Black Belt Certificate. This practitioner course for Six Sigma implementation provides extensive coverage of the Six Sigma process, as well as intensive exposure to the key analytical tools associated with Six Sigma, including project management, team skills, cost analysis, FMEA, basic statistics, inferential statistics, sampling, goodness of fit testing, regression and correlation analysis, reliability, design of experiments, statistical process control, measurement systems analysis, and simulation. Computer applications are emphasized.
NOTE: Participants must provide a windows based computer running Microsoft Office to the seminar.
More Info: https://viterbiexeced.usc.edu/engineering-program-areas/six-sigma-lean-certification/six-sigma-black-belt/
Audiences: Registered Attendees
Posted By: Corporate & Professional Programs
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AME Seminar
Sun, Aug 11, 2019 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Eckart Meiburg, UC Santa Barbara
Talk Title: Settling of Cohesive Sediment: Particle resolved Simulations
Abstract: We develop a physical and computational model for performing fully coupled, grain resolving Direct Numerical Simulations of cohesive sediment, based on the Immersed Boundary Method. The model distributes the cohesive forces over a thin shell surrounding each particle, thereby allowing for the spatial and temporal resolution of the cohesive forces during particle to particle interactions.
We test and validate the cohesive force model for binary particle interactions in the Drafting-Kissing-Tumbling aka DKT configuration. Cohesive sediment grains can remain attached to each other during the tumbling phase following the initial collision, thereby giving rise to the formation of flocs. The DKT simulations demonstrate that cohesive particle pairs settle in a preferred orientation, with particles of very different sizes preferentially aligning themselves in the vertical direction, so that the smaller particle is drafted in the wake of the larger one. This preferred orientation of cohesive particle pairs is found to remain influential for much larger simulations of 1,261 polydisperse particles released from rest. These simulations reproduce several earlier experimental observations by other authors, such as the accelerated settling of sand and silt particles due to particle bonding, the stratification of cohesive sediment deposits, and the consolidation process of the deposit. This final phase also shows the build-up of cohesive and direct contact intergranular stresses. The simulations demonstrate that cohesive forces accelerate the overall settling process primarily because smaller grains attach to larger ones and settle in their wakes. An investigation of the energy budget shows that the work of the collision forces substantially modifies the relevant energy conversion processes.
Biography: Eckart Meiburg received his Ph.D. from the University of Karlsruhe. After a postdoc at Stanford, he became an assistant professor in applied mathematics at Brown. He then moved to USC as associate then full professor. He later moved to UC Santa Barbara.
His research interests are fluid dynamics and transport phenomena, primarily computational fluid dynamics. He uses highly resolved direct numerical simulations to investigate physical mechanisms governing the spatio temporal evolution of a wide variety of geophysical, porous media, and multiphase flow fields. Some of his current interests are gravity and turbidity currents, Hele-Shaw displacements, double diffusive phenomena in particle laden flows, and internal bores.
Meiburg has received a Presidential Young Investigator Award, a Humboldt Senior Research Award, and a Senior Gledden Fellowship Institute of Advanced Studies, University of Western Australia. He is fellow of the American Physical Society and the ASME, was the 2012 Lorenz G. Straub Award Keynote Speaker at Univ. Minn., gave the Ronald F. Probstein Lecture at MIT in 2018, and was Shimizu Visiting Professor at Stanford University.
Host: Bermejo-Moreno
Location: SLH 102
Audiences: Everyone Is Invited
Posted By: Tessa Yao
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NL Seminar-COMPREHENSIBLE CONTEXT-DRIVEN TEXT GAME PLAYING
Thu, Aug 15, 2019 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Xusen Yin, USC/ISI
Talk Title: COMPREHENSIBLE CONTEXT-DRIVEN TEXT GAME PLAYING
Series: Natural Language Seminar
Abstract: In order to train a computer agent to play a text based computer game, we must represent each hidden state of the game. A Long Short Term Memory LSTM model running over observed texts is a common choice for state construction. However, a normal Deep Q learning Network DQN for such an agent requires millions of steps of training or more to converge. As such, an LSTM based DQN can take tens of days to finish the training process. Though we can use a Convolutional Neural Network CNN as a text encoder to construct states much faster than the LSTM, doing so without an understanding of the syntactic context of the words being analyzed can slow convergence. In this paper, we use a fast CNN to encode position and syntax-oriented structures extracted from observed texts as states. We additionally augment the reward signal in a universal and practical manner. Together, we show that our improvements can not only speed up the process by one order of magnitude but also learn a superior agent.
Biography: Xusen Yin is a 3rd-year Ph.D. student in USC ISI, advised by Dr. Jonathan May.
Host: Xusen Yin and Jon May
More Info: https://nlg.isi.edu/nl-seminar
Webcast: https://bluejeans.com/s/qXurzLocation: Information Science Institute (ISI) - CR #689
WebCast Link: https://bluejeans.com/s/qXurz
Audiences: Everyone Is Invited
Posted By: Peter Zamar
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Seminar
Wed, Aug 21, 2019 @ 10:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Peter Hofstee and Johan Peltenburg, Delft University of Technology, Netherlands
Talk Title: The Fletcher Framework, Bringing Apache Arrow to FPGAs
Abstract: Modern big data systems are highly heterogeneous. Components are implemented in a wide variety of programming languages and frameworks. Due to implementation differences, interfaces between components are burdened by serialization overhead. The Apache Arrow project helps to overcome this burden through a language-agnostic columnar in-memory format for big data applications. It is currently being integrated in many big data analytics frameworks, such as Apache Spark & Parquet, Dask, Pandas, etc...
The open-source Fletcher framework is an implementation of Arrow for FPGA accelerators. Through a design generation step, Fletcher takes Arrow data structures and generates specialized, high-performance and easy-to-use hardware interfaces that can connect to accelerator kernels. Serialization overhead is prevented, and integration with over 11 high-level languages is made possible and efficient.
After a brief introduction providing context for shared-memory heterogeneous computing using some of the current POWER systems as examples, we will go over the benefits of Apache Arrow and Fletcher, show a hands-on example, and discuss related projects, such as applying SQL queries to the Arrow datasets in FPGA, reading and decompressing Parquet files on the fly using FPGA, straight into host-system memory.
Biography: Peter Hofstee is a distinguished research staff member at IBM Austin, USA, and a part-time professor in Big Data Systems at Delft University of Technology, Netherlands. He is best known for his contributions to Heterogeneous computing as the chief architect of the Synergistic Processor Elements in the Cell Broadband Engine processor used in the Sony PlayStation 3, and the first supercomputer to reach sustained Petaflop operation. After returning to IBM research in 2011 he has focused on optimizing the system roadmap for big data, analytics, and cloud, including the use of accelerated computation. His early research work on coherently attached reconfigurable acceleration on POWER7 paved the way for the new coherent attach processor interface on POWER8. He holds more than 100 issued patents.
Johan Peltenburg is a PhD Candidate from the Delft University of Technology in The Netherlands. His research focuses on heterogeneous computing for big data applications. Johan received his B. Eng in Electrical Engineering at the Rotterdam University of Applied Science, followed by an M.Sc. in Computer Engineering at the Delft University of Technology. After spending some years in industry and as a teacher at the Rotterdam University of Applied science, Johan joined the Quantum & Computer Engineering department of the TU Delft in 2016, where he pursues his Ph.D. degree in Computer Engineering. He is currently working on the Fletcher FPGA accelerator framework within the Accelerated Big Data Systems group.
Host: Murali Annavaram
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Posted By: Estela Lopez
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Web Communities
Wed, Aug 21, 2019 @ 10:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Savvas Zannettou, Cyprus University of Technology
Talk Title: Web Communities
Abstract: The Web consists of numerous Web communities, news sources, and services, which are usually exploited by various entities for the dissemination of false information. Yet, we lack tools and techniques to effectively track the propagation of information across the multiple diverse communities and to capture and model the interplay between them. Also, we lack a basic understanding of what the role and impact of some emerging communities and services on the Web information ecosystem is, and more importantly, how such communities are exploited by bad actors (e.g., state- sponsored trolls) that spread false and weaponized information. In this talk, we will present numerous studies where we follow a data-driven cross-platform quantitative approach that analyzes billions of posts from Twitter, Reddit, 4chan Politically Incorrect board (/pol/), and Gab, to shed light into: 1) how news and image-based memes travel from one Web community to another and how we can model and quantify the influence between the various Web communities; 2) what is the role and impact of new emerging Web communities (e.g., Gab); and 3) how popular Web communities are exploited by state-sponsored actors for the sole purpose of spreading disinformation and sowing public discord.
Biography:
Savvas Zannettou is a PhD candidate from Cyprus University of Technology, co-advised by Dr. Michael Sirivianos and Dr. Jeremy Blackburn. In 2014 and 2016 he received respectively the BSc and
MSc degrees in Computer Engineering from Cyprus University of Technology. During 2014, he was a Research Intern at NEC Labs Europe for 6 months where he worked on Software-Defined Networks.
During 2017 and 2018, he was a Research Intern at Telefonica Research for 12 months. He is primarily interested in applying large-scale cross-platform quantitative analysis to understand emerging socio-technical issues like the spread of disinformation/misinformation and hateful content across the Web.
During his PhD, he received two first-author best paper awards: one at IMC 2018 and one at Cybersafety workshop (co-located with WWW).
Host: Shrikanth Narayanan (Viterbi), Emilion Ferrara (ISI)
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Posted By: Tanya Acevedo-Lam/EE-Systems
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AME Seminar
Wed, Aug 28, 2019 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Oscar Bruno, CalTech
Talk Title: Fast Spectral Time Domain PDE Solvers for Complex Structures: The Fourier Continuation Method
Abstract: We present fast spectral solvers for time-domain Partial Differential Equations. Based on a novel Fourier-Continuation (FC) method for the resolution of the Gibbs phenomenon, these methodologies give rise to time-domain solvers for PDEs for general engineering problems and structures. The methods enjoy a number of desirable properties, including spectral time evolution essentially free of pollution or dispersion errors for general PDEs in the time domain, with conditional unconditional stability for explicit alternating-direction methods and high order of temporal accuracy. A variety of applications to linear and nonlinear PDE problems will be presented, including the diffusion and wave equations, the Navier-Stokes equations and the elastic wave equation, demonstrating the significant improvements the new algorithms can provide over the accuracy and speed resulting from other approaches.
Biography: Oscar Bruno received his Ph.D. degree from the Courant Institute of Mathematical Sciences, New York University. Following graduation, he held a two-year position as Visiting Assistant Professor with the University of Minnesota, and he then joined the faculty of the Georgia Institute of Technology aka Georgia Tech, where he served as Assistant and Associate Professor. After a four-year period with Georgia Tech, in 1995 he joined the faculty of the California Institute of Technology aka Caltech, where he has served as Professor in the Department of Applied and Computational Mathematics since 1998, and as Executive Officer of that department during 1998-2000. Dr. Bruno has research interests that lie in areas of optics, elasticity and electromagnetism, remote sensing and radar, overall electromagnetic and elastic behavior of materials: solids, fluids, composites materials, multiplescale geometries, and phase transitions. Dr. Bruno has directed 37 graduate students and postdocs during his career, and his research efforts have resulted in the publication of more than 100 refereed articles, and have been acknowledged by his plenary presentations at many international conferences, his service on editorial boards of important scientific journals, including the SIAM Journal of Applied Mathematics, the SIAM Journal on Scientific Computing, and the Proceedings of the Royal Society of London, and his election to honorary societies, most notably the Council for the Society for Industrial and Applied Mathematics. Dr. Bruno is a recipient of the Sigma-Xi faculty award, the Friedrichs Award for an outstanding dissertation in mathematics, a Young Investigator Award from the National Science Foundation. and a Sloan Foundation Fellowship. Dr. Bruno is a SIAM Fellow in the class of 2013, and a National Security NSSEFF Vannevar Bush fellow, in the class of 2016.
Host: Pahlevan
Location: SLH 102
Audiences: Everyone Is Invited
Posted By: Tessa Yao
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CS Distinguished Lecture: Michael Stonebraker (MIT) - We Are Often Working on the Wrong Problem (10 Misconceptions About What is Important)
Thu, Aug 29, 2019 @ 03:30 PM - 04:50 PM
Computer Science
Conferences, Lectures, & Seminars
Speaker: Michael Stonebraker, MIT
Talk Title: We Are Often Working on the Wrong Problem (10 Misconceptions About What is Important)
Series: Computer Science Distinguished Lecture Series
Abstract: In the DBMS/Data Systems area, many of us seem to have lost our way. This talk discusses 10 different problem areas in which there is considerable current research. Then, I present why I believe much of the work is misguided, either because our assumptions about these problems are incorrect or because we are not paying attention to real users. Topics considered include machine learning (deep and conventional), public blockchain, data warehouses, schema evolution and the cloud.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Dr. Stonebraker has been a pioneer of data base research and technology for more than forty years. He was the main architect of the INGRES relational DBMS, and the object-relational DBMS, POSTGRES. These prototypes were developed at the University of California at Berkeley where Stonebraker was a Professor of Computer Science for twenty five years. More recently at M.I.T. he was a co-architect of the Aurora/Borealis stream processing engine, the C-Store column-oriented DBMS, the H-Store transaction processing engine, the SciDB array DBMS, and the Data Tamer data curation system. Presently he serves as Chief Technology Officer of Paradigm4 and Tamr, Inc.
Professor Stonebraker was awarded the ACM System Software Award in 1992 for his work on INGRES. Additionally, he was awarded the first annual SIGMOD Innovation award in 1994, and was elected to the National Academy of Engineering in 1997. He was awarded the IEEE John Von Neumann award in 2005 and the 2014 Turing Award, and is presently an Adjunct Professor of Computer Science at M.I.T.
Host: Shahram Ghandeharizadeh
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Posted By: Computer Science Department
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CS Colloquium: Filip Ilievski (Vrije Universiteit Amsterdam) - Identity of Long-tail Entities in Text: A Knowledge Perspective
Fri, Aug 30, 2019 @ 10:00 AM - 11:00 AM
Computer Science
Conferences, Lectures, & Seminars
Speaker: Filip Ilievski, Vrije Universiteit (VU) Amsterdam
Talk Title: Identity of Long-tail Entities in Text: A Knowledge Perspective
Series: Computer Science Colloquium
Abstract: Entity linking systems are faced with a complex M-to-N mapping between surface forms in text and instances in a knowledge base, caused by the ambiguity of surface forms, the variance of the instances, and their frequency/popularity interplays, well-explained by pragmatic principles such as the Gricean maxims (Grice, 1975). Although current entity linkers report high accuracy scores, in this talk I will describe phenomena that capture large differences in performance between 'head' and 'tail' entities. To improve performance on the tail entities, I will argue that we need: to revisit evaluation (part I) and to employ knowledge and reason over it in a more systematic way (part II).
During the first half, I will depict how the current evaluation datasets, as well as the metrics employed, obfuscate the difference between head and tail, and discourages focus on tail entities. I will propose recommended actions and examples for long-tail-focused evaluation.
In the second half of my talk, I will present our efforts to generate expectations on long-tail entities through building neural profiling machines on top of background knowledge from Wikidata. In addition to an intrinsic evaluation, these profiling techniques are evaluated extrinsically on clustering NIL entities. I will discuss how an extension of this work can be used to capture commonsense knowledge and act as an active component in future reading machines.
This lecture satisfies requirements for CSCI 591: Research Colloquium. Please note, due to limited capacity in RTH 105, seats will be first come first serve.
Biography: Filip Ilievski is a Postdoctoral Researcher in Natural Language Processing at Vrije Universiteit (VU) Amsterdam, and closely affiliated with the Knowledge Representation and Reasoning group at the same University. His research investigates how systematic and extensive use of knowledge can help machines to deal with the 'long-tail' (knowledge scarcity and ambiguity) of human communication. To do so, he combines ideas from Information Extraction, Knowledge Graphs, and Machine Learning.
He developed LOTUS (Ilievski et al., 2016a), the largest publicly available index over the Linked Data cloud at the time, which received an award at the Semantics conference in 2016. Later, he collaborated with prof. Ed Hovy at CMU on building neural generalization models ('profiling machines') over Linked Data knowledge and applying them to cluster long-tail entities. As part of his research on measuring and improving biases in NLP evaluations, he co-organized a SemEval competition on 'Counting Events and Participants in the Long Tail' in 2018 (Ilievski et al., 2016b, Postma et al., 2018).
Filip Ilievski authored over 20 publications about these topics in peer-reviewed international journals and conference proceedings, including COLING, ESWC, and SWJ.
Host: Xiang Ren
Location: Ronald Tutor Hall of Engineering (RTH) - 105
Audiences: Everyone Is Invited
Posted By: Computer Science Department
