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Events for December 05, 2023

  • VLP Festive Finals Study Slam Day 2

    Tue, Dec 05, 2023 @ 10:00 AM - 05:00 PM

    Viterbi School of Engineering Student Affairs

    Student Activity


    Do finals have you feeling frosty? Get cozy at the VLP during our Festive Finals Study Slam! Warm up in our public or private study spaces, eat tasty festive treats, and grab some giveaways that will help you deck the halls with great grades! 

    Location: Ronald Tutor Hall of Engineering (RTH) - 222

    Audiences: Everyone Is Invited

    Contact: Alex Bronz

    Event Link: https://cglink.me/2nB/r393530

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  • PhD Thesis Defense - Gautam Salhotra

    Tue, Dec 05, 2023 @ 03:00 PM - 05:00 PM

    Thomas Lord Department of Computer Science

    University Calendar


    PhD Thesis Defense - Gautam Salhotra
     
    Committee Members: Gaurav Sukhatme (chair), Somil Bansal, Daniel Seita
     
    Title: Accelerating Robot Manipulation with demonstrations
     
    Abstract: Robot manipulation of complex objects, such as cloth, is challenging due to difficulties in perceiving and exploring the environment. Pure reinforcement learning (RL) is difficult in this setting, as it requires extensive exploration of the state space, which can be inefficient and dangerous. Demonstrations from humans can alleviate the need for exploration, but collecting good demonstrations can be time-consuming and expensive. Therefore, a good balance between perception, exploration, and imitation is needed to solve manipulation of complex objects.This thesis focuses on dexterous manipulation of complex objects, such as cloth, using images and without assuming full state information during inference. It also aims to achieve efficient learning by reducing interactions with the environment during exploration and reducing the overhead of collecting demonstrations. To achieve these goals, we present i. a learning algorithm that uses a motion planner in the loop, to enable efficient long horizon exploration, ii. A framework for visual manipulation of complex deformable objects using demonstrations from a set of agents with different embodiments. iii. An LfD algorithm for dexterous tasks with rigid objects, such as peg insertion with high precision, using images and a multi-task attention-based architecture.These contributions enable robots to manipulate complex objects efficiently and with high precision, using images alone. This opens up new possibilities for robots to be used in a wider range of applications, such as manufacturing, logistics, and healthcare

    Location: Ronald Tutor Hall of Engineering (RTH) - 406

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

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  • CS Colloquium: Yitao Liang - Towards Generalist Agents in a Open-World Environment

    Tue, Dec 05, 2023 @ 04:00 PM - 05:50 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Yitao Liang, Peking University

    Talk Title: Towards Generalist Agents in a Open-World Environment

    Abstract: With the advent of large language models, the debate about whether generalist agents are coming resurges. It maybe an over ambitious goal. Yet, to make any progress, we need an appropriate testing bed accompanied with principled evaluation protocols. In our past findings, we noticed that the prior testing beds for agents are mostly designed to have one specific task and goal (sometimes specified by one reward function). This greatly limits our ability to benchmark whether we are making significant progress in building a generalist agent. In this tutorial, we will introduce the comprehensive efforts from my group and a few other related prominent research labs of using open-world environments (e.g., Minecraft) to target generalist agents. We will dig into why now it is a good time to do the switch; what are the characteristics of those environments; what are the unique challenges to them and how addressing those challenges are indispensable from generalist agents; and lastly, how the latest research in this area is reshaping our community
     
    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Yitao Liang is an assistant professor at Peking University. He obtained his Ph.D. degree in Computer Science from UCLA, advised by Prof. Guy Van den Broeck. His research interests span knowledge reasoning and machine learning.His work has received recognition from top AI conferences; for example, the best-paper honorable mention from AAMAS 2016, the best paper from RL for Real Life workshop in ICML 2019, a best paper runner-up from the LLD workshop in NeurIPS 2017, a best paper from the TEACH workshop in ICML2023. He regularly serves as area chairs in top venues. Recently, his group Team CraftJarvis (craftjarvis.org) is taking a neural-symbolic approach to building a generalist agents in open-world environments

    Host: Jieyu Zhao

    Location: Olin Hall of Engineering (OHE) - 136

    Audiences: Everyone Is Invited

    Contact: Melissa Ochoa

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