Research Projects - Artificial Intelligence (AI)
Large Projects
- Algorithms and Frameworks for OCR and Content-based Image Retrieval
Jike Chong, Bryan Christopher Catanzaro, Narayanan Sundaram, Fares Hedayati and Kurt Keutzer - Bioinformatics
Michael Jordan - Center for Biomedical Informatics in Critical Care (C-BICC)
Norman Aleks, Stuart J. Russell, Shaunak Chatterjee, Nimar S Arora and Geoffrey Manley - Declarative Systems Programming
Joseph M. Hellerstein - Directing a Datacenter
Peter Bodik, Charles Sutton, Armando Fox, David A. Patterson and Michael Jordan - Effective Bayesian Transfer Learning (EBTL)
Stuart J. Russell, Peter Bartlett and Michael Jordan - GamesCrafters: Undergraduate Game Theory Research and Development
Dan Garcia - Natural Language Processing Group (NLP)
Daniel Klein, Alexandre Bouchard-Cote, John Sturdy DeNero, Aria Delier Haghighi, Percy Shuo Liang, Adam David Pauls, Slav Orlinov Petrov and David Burkett - Recognition using Regions
Jitendra Malik, Chunhui Gu, Pablo Arbelaez and Joseph Lim - Statistical Analysis of Online News (StatNews)
Laurent El Ghaoui, Bin Yu, Alexandre d'Aspremont and Brian Christopher Gawalt - Statistical Machine Learning
Michael Jordan, Lior Pachter, Peter Bartlett and Martin Wainwright - The Stanford/Berkeley Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC)
Haomiao Huang, Michael Vitus, Jeremy Gillula, Patrick Bouffard, Eugene Li, Tony Mercer, Christopher Berner and Claire Tomlin
Small Projects
- A General Framework for Workload Evaluation
Kristal Sauer, Charles Reiss, Alexandra Constantin, Archana Sulochana Ganapathi, Armando Fox, David A. Patterson and Michael Jordan - A Probabilistic Approach to Diachronic Phonology
Alexandre Bouchard-Cote, Percy Shuo Liang, Daniel Klein and Thomas Griffiths - A Stochastic View of Optimal Regret through Minimax Duality
Jacob Abernethy, Alekh Agarwal, Peter Bartlett and Alexander Rakhlin - Agreement-based Learning
Percy Shuo Liang, Daniel Klein and Michael Jordan - Angelic Hierarchical Planning
Jason Wolfe, Stuart J. Russell and Bhaskara Marthi - Classification of Images with Hierarchical Beta Processes
Romain Jean Thibaux, Michael Jordan and Erik Sudderth - Computational complexity of statistical estimation
Alekh Agarwal, Peter Bartlett, Pradeep Ravikumar and Martin Wainwright - CPRMs: A Joint Model for Understanding and Action
Leon Rubin Barrett and Jerome A. Feldman - Data-Parallel Large Vocabulary Continuous Speech Recognition on Manycore Processors
Jike Chong, Yi Youngmin, Arlo Faria, Nadathur Rajagopalan Satish and Kurt Keutzer - DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
Simon Lacoste-Julien, Fei Sha and Michael Jordan - Discriminative Features for Large Vocabulary Speech Recognition
Arlo Faria, Nelson Morgan and Suman Ravuri - Exploring Intrinsic Speaker Qualities Via an Analysis of Automatic Speaker Recognition Systems
Lara Stoll and Nelson Morgan - Facial Image Indexing Interfaces
Trevor Darrell and Ashley Michelle Eden - Grammar Learning Using Bayesian Nonparametrics
Percy Shuo Liang, Slav Orlinov Petrov, Michael Jordan and Daniel Klein - Hashing Algorithms for Scalable Image Search
Brian Kulis and Trevor Darrell - High-dimensional subset recovery in noise: Sparsified measurements without loss of statistical efficiency
Christian Ladapo Omidiran and Martin Wainwright - Jointly Constraining Parsing and Word Alignment on Bitexts
David Burkett, John Blitzer and Daniel Klein - Learning and Inference for Hierarchically Split Probabilistic Context-Free Grammars
Slav Orlinov Petrov and Daniel Klein - Learning for robotics
Pieter Abbeel - Learning to Identify Locally Actionable Health Anomalies
Kuang Chen, Emma Brunskill, Joseph M. Hellerstein and Tapan Parikh - Local Probabilistic Regression for Activity-Independent Human Pose Inference
Trevor Darrell and Raquel Urtasun - Modeling events in continuous time.
Aleksandr Simma and Michael Jordan - Multi-Modal Learning and Sensing for Mobile Robotic Systems
Mario Fritz and Trevor Darrell - Multi-stream speech recognition
Nelson Morgan and Suman Ravuri - Multi-View Learning in the Presence of View Disagreement
Trevor Darrell, C. Mario Christhoudias and Raquel Urtasun - Multiprocessor Implementation of Image Recognition
Narayanan Sundaram, Bryan Christopher Catanzaro, Jike Chong and Kurt Keutzer - Nonparametric Bayesian Methods for Machine Learning
Romain Jean Thibaux and Michael Jordan - Nonrigid Object Recognition and Tracking
Mathieu Salzmann, Trevor Darrell and Yangqing Jia - Object Category Recognition Using Probabilistic Fusion of Speech and Image Classifiers
Trevor Darrell and Kate Saenko - Parallel MLP Feature Extraction for Speech Recognition
Nelson Morgan, Chris Oei, Sherry Zhao and Adam Janin - Perceptually Grounded Spatial Semantics
David Golland, Daniel Klein and Trevor Darrell - Portfolio Effects in Collaborative Filtering
Tavi Nathanson, Ephrat Bitton and Ken Goldberg - Privacy-Preserving Support Vector Learning
Benjamin I. P. Rubinstein, Peter Bartlett, Ling Huang and Nina Taft - Probabilistic Inference with Unknown Objects
Stuart J. Russell, Rodrigo de Salvo Braz and Nimar S Arora - Properties of Maximum and Maximal VC-Classes
Benjamin I. P. Rubinstein, J. Hyam Rubinstein and Peter Bartlett - Prototype Sequence Modeling Toolkit (Prototypes)
Aria Delier Haghighi and Daniel Klein - Security of Adaptive Systems (SecML)
Blaine Alan Nelson, Benjamin I. P. Rubinstein, Anthony D. Joseph, Doug Tygar, Jack Chi, Satish Rao, Nina Taft, Ling Huang, Shing-hon Lau and Anthony Tran - Statistical Analysis of Estimators in Machine Learning
Percy Shuo Liang and Michael Jordan - Syntactic Machine Translation
Alexandre Bouchard-Cote, John Sturdy DeNero, Aria Delier Haghighi, Percy Shuo Liang and Daniel Klein - Transparent Local Features for Object Recognition
Mario Fritz, Sergey Karayev and Trevor Darrell - Unsupervised Content-Based Organization of Large Collections of Activity Videos
Parvez Ahammad, Chuohao Yeo, Kannan Ramchandran and S. Shankar Sastry - Unsupervised Coreference Resolution (UnsupCoref)
Aria Delier Haghighi and Daniel Klein - Unsupervised Learning of Visual Sense Models for Polysemous Words
Trevor Darrell and Kate Saenko - Unsupervised Word Alignments for Machine Translation
John Sturdy DeNero, Percy Shuo Liang, Daniel Klein and Ben Taskar - Using Control Theory to Make Safety Guarantees About Learned Dynamics and Behaviors
Jeremy Gillula and Claire Tomlin
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