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Author Information
Gal Chechik (NVIDIA, Bar-Ilan University)
Geremy Heitz (Stanford University)
Gal Elidan (Hebrew University)
Pieter Abbeel (UC Berkeley & Covariant)
Pieter Abbeel is Professor and Director of the Robot Learning Lab at UC Berkeley [2008- ], Co-Director of the Berkeley AI Research (BAIR) Lab, Co-Founder of covariant.ai [2017- ], Co-Founder of Gradescope [2014- ], Advisor to OpenAI, Founding Faculty Partner AI@TheHouse venture fund, Advisor to many AI/Robotics start-ups. He works in machine learning and robotics. In particular his research focuses on making robots learn from people (apprenticeship learning), how to make robots learn through their own trial and error (reinforcement learning), and how to speed up skill acquisition through learning-to-learn (meta-learning). His robots have learned advanced helicopter aerobatics, knot-tying, basic assembly, organizing laundry, locomotion, and vision-based robotic manipulation. He has won numerous awards, including best paper awards at ICML, NIPS and ICRA, early career awards from NSF, Darpa, ONR, AFOSR, Sloan, TR35, IEEE, and the Presidential Early Career Award for Scientists and Engineers (PECASE). Pieter's work is frequently featured in the popular press, including New York Times, BBC, Bloomberg, Wall Street Journal, Wired, Forbes, Tech Review, NPR.
Daphne Koller (insitro)
Daphne Koller is the Rajeev Motwani Professor of Computer Science at Stanford University and the co-founder and co-CEO of Coursera, a social entrepreneurship company that works with the best universities to connect anyone around the world with the best education, for free. Coursera is the leading MOOC (Massive Open Online Course) platform, and has partnered with dozens of the world’s top universities to offer hundreds of courses in a broad range of disciplines to millions of students, spanning every country in the world. In her research life, she works in the area of machine learning and probabilistic modeling, with applications to systems biology and personalized medicine. She is the author of over 200 refereed publications in venues that span a range of disciplines, and has given over 15 keynote talks at major conferences. She is the recipient of many awards, which include the Presidential Early Career Award for Scientists and Engineers (PECASE), the MacArthur Foundation Fellowship, the ACM/Infosys award, and membership in the US National Academy of Engineering. She is also an award winning teacher, who pioneered in her Stanford class many of the ideas that underlie the Coursera user experience. She received her BSc and MSc from the Hebrew University of Jerusalem, and her PhD from Stanford in 1994.
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2021 : Hierarchical Few-Shot Imitation with Skill Transition Models »
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2021 : Pretraining for Language-Conditioned Imitation with Transformers »
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2022 : Multi-Environment Pretraining Enables Transfer to Action Limited Datasets »
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2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
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2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
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2022 : SoftTreeMax: Policy Gradient with Tree Search »
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2023 Poster: Language Quantized AutoEncoders for Data Efficient Text-Image Alignment »
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2023 Poster: Point Cloud Completion with Pretrained Text-to-Image Diffusion Models »
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2023 Poster: Norm-guided latent space exploration for text-to-image generation »
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2023 Poster: Learning Universal Policies via Text-Guided Video Generation »
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2023 Poster: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation »
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2023 Poster: Blockwise Parallel Transformer for Large Models »
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2023 Poster: Video Prediction Models as Rewards for Reinforcement Learning »
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2023 Poster: Syntactic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment »
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2023 Poster: Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration »
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2023 Poster: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models »
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2023 Poster: Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? »
Arjun Majumdar · Karmesh Yadav · Sergio Arnaud · Jason Yecheng Ma · Claire Chen · Sneha Silwal · Aryan Jain · Vincent-Pierre Berges · Tingfan Wu · Jay Vakil · Pieter Abbeel · Jitendra Malik · Dhruv Batra · Yixin Lin · Oleksandr Maksymets · Aravind Rajeswaran · Franziska Meier -
2023 Oral: Syntactic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment »
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2022 : Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs »
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2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
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2022 : Train Offline, Test Online: A Real Robot Learning Benchmark »
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2022 Poster: On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning »
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2022 Poster: Chain of Thought Imitation with Procedure Cloning »
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2022 Poster: Masked Autoencoding for Scalable and Generalizable Decision Making »
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2022 Poster: Deep Hierarchical Planning from Pixels »
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2021 : Playful Interactions for Representation Learning »
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2021 Poster: Hindsight Task Relabelling: Experience Replay for Sparse Reward Meta-RL »
Charles Packer · Pieter Abbeel · Joseph Gonzalez -
2021 Poster: Improving Computational Efficiency in Visual Reinforcement Learning via Stored Embeddings »
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2021 : BASALT: A MineRL Competition on Solving Human-Judged Task + Q&A »
Rohin Shah · Cody Wild · Steven Wang · Neel Alex · Brandon Houghton · William Guss · Sharada Mohanty · Stephanie Milani · Nicholay Topin · Pieter Abbeel · Stuart Russell · Anca Dragan -
2021 Poster: Decision Transformer: Reinforcement Learning via Sequence Modeling »
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2021 Poster: Personalized Federated Learning With Gaussian Processes »
Idan Achituve · Aviv Shamsian · Aviv Navon · Gal Chechik · Ethan Fetaya -
2021 Poster: Mastering Atari Games with Limited Data »
Weirui Ye · Shaohuai Liu · Thanard Kurutach · Pieter Abbeel · Yang Gao -
2021 Poster: Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction »
Gal Dalal · Assaf Hallak · Steven Dalton · iuri frosio · Shie Mannor · Gal Chechik -
2021 Poster: Reinforcement Learning with Latent Flow »
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2021 Poster: Behavior From the Void: Unsupervised Active Pre-Training »
Hao Liu · Pieter Abbeel -
2021 Poster: Teachable Reinforcement Learning via Advice Distillation »
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2020 : Panel discussion »
Pierre-Yves Oudeyer · Marc Bellemare · Peter Stone · Matt Botvinick · Susan Murphy · Anusha Nagabandi · Ashley Edwards · Karen Liu · Pieter Abbeel -
2020 : Contributed Talk: Reset-Free Lifelong Learning with Skill-Space Planning »
Kevin Lu · Aditya Grover · Pieter Abbeel · Igor Mordatch -
2020 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · Chelsea Finn · Joelle Pineau · David Silver · Satinder Singh · Coline Devin · Misha Laskin · Kimin Lee · Janarthanan Rajendran · Vivek Veeriah -
2020 Poster: Denoising Diffusion Probabilistic Models »
Jonathan Ho · Ajay Jain · Pieter Abbeel -
2020 Poster: Automatic Curriculum Learning through Value Disagreement »
Yunzhi Zhang · Pieter Abbeel · Lerrel Pinto -
2020 Poster: AvE: Assistance via Empowerment »
Yuqing Du · Stas Tiomkin · Emre Kiciman · Daniel Polani · Pieter Abbeel · Anca Dragan -
2020 Poster: A causal view of compositional zero-shot recognition »
Yuval Atzmon · Felix Kreuk · Uri Shalit · Gal Chechik -
2020 Spotlight: A causal view of compositional zero-shot recognition »
Yuval Atzmon · Felix Kreuk · Uri Shalit · Gal Chechik -
2020 Poster: Reinforcement Learning with Augmented Data »
Misha Laskin · Kimin Lee · Adam Stooke · Lerrel Pinto · Pieter Abbeel · Aravind Srinivas -
2020 Poster: Generalized Hindsight for Reinforcement Learning »
Alexander Li · Lerrel Pinto · Pieter Abbeel -
2020 Poster: Trajectory-wise Multiple Choice Learning for Dynamics Generalization in Reinforcement Learning »
Younggyo Seo · Kimin Lee · Ignasi Clavera Gilaberte · Thanard Kurutach · Jinwoo Shin · Pieter Abbeel -
2020 Spotlight: Reinforcement Learning with Augmented Data »
Misha Laskin · Kimin Lee · Adam Stooke · Lerrel Pinto · Pieter Abbeel · Aravind Srinivas -
2020 Poster: Sparse Graphical Memory for Robust Planning »
Scott Emmons · Ajay Jain · Misha Laskin · Thanard Kurutach · Pieter Abbeel · Deepak Pathak -
2020 Poster: Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model »
Alex X. Lee · Anusha Nagabandi · Pieter Abbeel · Sergey Levine -
2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · Chelsea Finn · Joelle Pineau · David Silver · Satinder Singh · Joshua Achiam · Carlos Florensa · Christopher Grimm · Haoran Tang · Vivek Veeriah -
2019 : Pieter Abbeel »
Pieter Abbeel -
2019 : In conversations: Daphne Koller and Barbara Englehardt »
Daphne Koller · Barbara Engelhardt -
2019 Poster: Evaluating Protein Transfer Learning with TAPE »
Roshan Rao · Nicholas Bhattacharya · Neil Thomas · Yan Duan · Peter Chen · John Canny · Pieter Abbeel · Yun Song -
2019 Spotlight: Evaluating Protein Transfer Learning with TAPE »
Roshan Rao · Nicholas Bhattacharya · Neil Thomas · Yan Duan · Peter Chen · John Canny · Pieter Abbeel · Yun Song -
2019 Poster: Goal-conditioned Imitation Learning »
Yiming Ding · Carlos Florensa · Pieter Abbeel · Mariano Phielipp -
2019 Poster: Geometry-Aware Neural Rendering »
Joshua Tobin · Wojciech Zaremba · Pieter Abbeel -
2019 Poster: MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies »
Xue Bin Peng · Michael Chang · Grace Zhang · Pieter Abbeel · Sergey Levine -
2019 Oral: Geometry-Aware Neural Rendering »
Joshua Tobin · Wojciech Zaremba · Pieter Abbeel -
2019 Poster: Compositional Plan Vectors »
Coline Devin · Daniel Geng · Pieter Abbeel · Trevor Darrell · Sergey Levine -
2019 Poster: On the Utility of Learning about Humans for Human-AI Coordination »
Micah Carroll · Rohin Shah · Mark Ho · Tom Griffiths · Sanjit Seshia · Pieter Abbeel · Anca Dragan -
2019 Poster: Compression with Flows via Local Bits-Back Coding »
Jonathan Ho · Evan Lohn · Pieter Abbeel -
2019 Poster: Guided Meta-Policy Search »
Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn -
2019 Spotlight: Compression with Flows via Local Bits-Back Coding »
Jonathan Ho · Evan Lohn · Pieter Abbeel -
2019 Spotlight: Guided Meta-Policy Search »
Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn -
2018 : Pieter Abbeel »
Pieter Abbeel -
2018 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · David Silver · Satinder Singh · Joelle Pineau · Joshua Achiam · Rein Houthooft · Aravind Srinivas -
2018 Poster: Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction »
Roei Herzig · Moshiko Raboh · Gal Chechik · Jonathan Berant · Amir Globerson -
2018 Poster: Meta-Reinforcement Learning of Structured Exploration Strategies »
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine -
2018 Poster: Learning Plannable Representations with Causal InfoGAN »
Thanard Kurutach · Aviv Tamar · Ge Yang · Stuart Russell · Pieter Abbeel -
2018 Spotlight: Meta-Reinforcement Learning of Structured Exploration Strategies »
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine -
2018 Poster: Evolved Policy Gradients »
Rein Houthooft · Yuhua Chen · Phillip Isola · Bradly Stadie · Filip Wolski · OpenAI Jonathan Ho · Pieter Abbeel -
2018 Spotlight: Evolved Policy Gradients »
Rein Houthooft · Yuhua Chen · Phillip Isola · Bradly Stadie · Filip Wolski · OpenAI Jonathan Ho · Pieter Abbeel -
2018 Poster: The Importance of Sampling inMeta-Reinforcement Learning »
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2017 : Meta-Learning Shared Hierarchies (Pieter Abbeel) »
Pieter Abbeel -
2017 : Exhausting the Sim with Domain Randomization and Trying to Exhaust the Real World, Pieter Abbeel, UC Berkeley and Embodied Intelligence »
Pieter Abbeel · Gregory Kahn -
2017 Symposium: Deep Reinforcement Learning »
Pieter Abbeel · Yan Duan · David Silver · Satinder Singh · Junhyuk Oh · Rein Houthooft -
2017 Poster: #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning »
Haoran Tang · Rein Houthooft · Davis Foote · Adam Stooke · OpenAI Xi Chen · Yan Duan · John Schulman · Filip DeTurck · Pieter Abbeel -
2017 Poster: Inverse Reward Design »
Dylan Hadfield-Menell · Smitha Milli · Pieter Abbeel · Stuart J Russell · Anca Dragan -
2017 Oral: Inverse Reward Design »
Dylan Hadfield-Menell · Smitha Milli · Pieter Abbeel · Stuart J Russell · Anca Dragan -
2017 Invited Talk: Deep Learning for Robotics »
Pieter Abbeel -
2017 Demonstration: Deep Robotic Learning using Visual Imagination and Meta-Learning »
Chelsea Finn · Frederik Ebert · Tianhe Yu · Annie Xie · Sudeep Dasari · Pieter Abbeel · Sergey Levine -
2017 Poster: One-Shot Imitation Learning »
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2016 : CV @ Scale Challenges »
Manohar Paluri · Gal Chechik -
2016 Workshop: Large Scale Computer Vision Systems »
Manohar Paluri · Lorenzo Torresani · Gal Chechik · Dario Garcia · Du Tran -
2016 : Pieter Abbeel (University of California, Berkeley) »
Pieter Abbeel -
2016 : Invited Talk: Safe Reinforcement Learning for Robotics (Pieter Abbeel, UC Berkeley and OpenAI) »
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2016 Workshop: Deep Reinforcement Learning »
David Silver · Satinder Singh · Pieter Abbeel · Peter Chen -
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2016 Poster: Combinatorial Energy Learning for Image Segmentation »
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2016 Poster: InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets »
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2016 Poster: VIME: Variational Information Maximizing Exploration »
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2016 Poster: Value Iteration Networks »
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2016 Oral: Value Iteration Networks »
Aviv Tamar · Sergey Levine · Pieter Abbeel · YI WU · Garrett Thomas -
2016 Poster: Cooperative Inverse Reinforcement Learning »
Dylan Hadfield-Menell · Stuart J Russell · Pieter Abbeel · Anca Dragan -
2016 Tutorial: Deep Reinforcement Learning Through Policy Optimization »
Pieter Abbeel · John Schulman -
2015 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · John Schulman · Satinder Singh · David Silver -
2015 Poster: Gradient Estimation Using Stochastic Computation Graphs »
John Schulman · Nicolas Heess · Theophane Weber · Pieter Abbeel -
2014 Workshop: Novel Trends and Applications in Reinforcement Learning »
Csaba Szepesvari · Marc Deisenroth · Sergey Levine · Pedro Ortega · Brian Ziebart · Emma Brunskill · Naftali Tishby · Gerhard Neumann · Daniel Lee · Sridhar Mahadevan · Pieter Abbeel · David Silver · Vicenç Gómez -
2014 Workshop: Analyzing the omics of the brain »
Michael Hawrylycz · Gal Chechik · Mark Reimers -
2014 Poster: Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics »
Sergey Levine · Pieter Abbeel -
2014 Spotlight: Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics »
Sergey Levine · Pieter Abbeel -
2013 Invited Talk: The Online Revolution: Learning without Limits »
Daphne Koller -
2012 Poster: Shifting Weights: Adapting Object Detectors from Image to Video »
Kevin Tang · Vignesh Ramanathan · Li Fei-Fei · Daphne Koller -
2012 Poster: Nonparanormal Belief Propagation (NPBP) »
Gal Elidan · Cobi Cario -
2012 Poster: Near Optimal Chernoff Bounds for Markov Decision Processes »
Teodor Mihai Moldovan · Pieter Abbeel -
2012 Spotlight: Near Optimal Chernoff Bounds for Markov Decision Processes »
Teodor Mihai Moldovan · Pieter Abbeel -
2011 Workshop: Copulas in Machine Learning »
Gal Elidan · Zoubin Ghahramani · John Lafferty -
2011 Poster: Active Classification based on Value of Classifier »
Tianshi Gao · Daphne Koller -
2011 Spotlight: Active Classification based on Value of Classifier »
Tianshi Gao · Daphne Koller -
2010 Spotlight: On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient »
Jie Tang · Pieter Abbeel -
2010 Spotlight: Online Learning in The Manifold of Low-Rank Matrices »
Uri Shalit · Daphna Weinshall · Gal Chechik -
2010 Poster: Copula Bayesian Networks »
Gal Elidan -
2010 Poster: On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient »
Jie Tang · Pieter Abbeel -
2010 Poster: Online Learning in The Manifold of Low-Rank Matrices »
Uri Shalit · Daphna Weinshall · Gal Chechik -
2010 Poster: Self-Paced Learning for Latent Variable Models »
M. Pawan Kumar · Benjamin D Packer · Daphne Koller -
2009 Workshop: Machine Learning in Computational Biology »
Gal Chechik · Tomer Hertz · William S Noble · Yanjun Qi · Jean-Philippe Vert · Alexander Zien -
2009 Mini Symposium: Machine Learning in Computational Biology »
Yanjun Qi · Jean-Philippe Vert · Gal Chechik · Alexander Zien · Tomer Hertz · William S Noble -
2009 Poster: Region-based Segmentation and Object Detection »
Stephen Gould · Tianshi Gao · Daphne Koller -
2009 Spotlight: Region-based Segmentation and Object Detection »
Stephen Gould · Tianshi Gao · Daphne Koller -
2009 Poster: Learning a Small Mixture of Trees »
M. Pawan Kumar · Daphne Koller -
2009 Poster: An Online Algorithm for Large Scale Image Similarity Learning »
Gal Chechik · Uri Shalit · Varun Sharma · Samy Bengio -
2008 Workshop: Machine Learning in Computational Biology »
Gal Chechik · Christina Leslie · Quaid Morris · William S Noble · Gunnar Rätsch -
2008 Mini Symposium: Machine Learning in Computational Biology »
Gal Chechik · Christina Leslie · Quaid Morris · William S Noble · Gunnar Rätsch -
2008 Oral: Cascaded Classification Models: Combining Models for Holistic Scene Understanding »
Geremy Heitz · Stephen Gould · Ashutosh Saxena · Daphne Koller -
2008 Poster: Cascaded Classification Models: Combining Models for Holistic Scene Understanding »
Geremy Heitz · Stephen Gould · Ashutosh Saxena · Daphne Koller -
2008 Poster: Learning Bounded Treewidth Bayesian Networks »
Gal Elidan · Stephen Gould -
2008 Spotlight: Learning Bounded Treewidth Bayesian Networks »
Gal Elidan · Stephen Gould -
2008 Poster: LOOPS: Localizing Object Outlines using Probabilistic Shape »
Geremy Heitz · Gal Elidan · Benjamin D Packer · Daphne Koller -
2007 Workshop: Machine Learning in Computational Biology (Part 2) »
Gal Chechik · Christina Leslie · Quaid Morris · William S Noble · Gunnar Rätsch · Koji Tsuda -
2007 Workshop: Machine Learning in Computational Biology (Part 1) »
Gal Chechik · Christina Leslie · Quaid Morris · William S Noble · Gunnar Rätsch · Koji Tsuda -
2007 Demonstration: Holistic Scene Understanding from Visual and Range Data »
Stephen Gould · Morgan Quigley · Andrew Y Ng · Daphne Koller -
2007 Spotlight: Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion »
J. Zico Kolter · Pieter Abbeel · Andrew Y Ng -
2007 Poster: Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion »
J. Zico Kolter · Pieter Abbeel · Andrew Y Ng -
2006 Workshop: New Problems and Methods in Computational Biology »
Gal Chechik · Quaid Morris · Koji Tsuda · Gunnar Rätsch · Christina Leslie · William S Noble -
2006 Poster: Max-margin classification of incomplete data »
Gal Chechik · Geremy Heitz · Gal Elidan · Pieter Abbeel · Daphne Koller -
2006 Poster: Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Task »
Alexis Battle · Gal Chechik · Daphne Koller -
2006 Talk: Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Task »
Alexis Battle · Gal Chechik · Daphne Koller -
2006 Poster: An Application of Reinforcement Learning to Aerobatic Helicopter Flight »
Pieter Abbeel · Adam P Coates · Andrew Y Ng · Morgan Quigley -
2006 Poster: Using Combinatorial Optimization within Max-Product Belief Propagation »
John Duchi · Danny Tarlow · Gal Elidan · Daphne Koller -
2006 Spotlight: Using Combinatorial Optimization within Max-Product Belief Propagation »
John Duchi · Danny Tarlow · Gal Elidan · Daphne Koller -
2006 Talk: An Application of Reinforcement Learning to Aerobatic Helicopter Flight »
Pieter Abbeel · Adam P Coates · Andrew Y Ng · Morgan Quigley -
2006 Poster: Efficient Structure Learning of Markov Networks using L1-Regularization »
Su-In Lee · Varun Ganapathi · Daphne Koller