Courses
Fall 2006
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CS 294-2 Markov Chain Monte Carlo: Foundations and Applications (Presentation) -- Prof. Alistair Sinclair |
Spring 2006
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CS 294-5 Great Algorithms -- Prof. Richard Karp |
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MATH 225B Metamathematics -- Prof. Thomas Scanlon |
Fall 2005
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CS 294-10 Transfer Learning (report) -- Profs. Peter Bartlett, Mike Jordan and Stuart Russell |
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MATH 225A Metamathematics -- Prof. Jack Silver |
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STAT 212A Information Theory and Statistics -- Prof. Bin Yu |
Spring 2005
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CS 252 Graduate Computer Architecture (Project page) -- Prof. David Culler |
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STAT 210B Theoretical Statistics -- Prof. Mark van der Laan |
Fall 2004
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STAT 210A Theoretical Statistics -- Prof. C. S. Cheng |
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STAT 260 Probability on Trees and Networks -- Prof. Yuval Peres |
Spring 2004
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CS 270 Combinatorial Algorithms and Data Structures (report) -- Prof. Satish Rao |
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STAT 205B Probability Theory -- Prof. David Aldous |
Fall 2003
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CS 281A Statistical Learning Theory (report) (Poster Presentation) -- Prof. Peter Bartlett |
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SANSKR 100A Elementary Sanskrit -- Prof. Sally Goldman |
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STAT 205A Probability Theory -- Prof. David Aldous |
Spring 2003
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CS 182/Ling 109 Neural Basis of Thought and Language (report) -- Prof. Jerry Feldman |
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CS 281B Advanced Topics in Learning and Decision Making (Project Presentation) (report) -- Prof. Peter Bartlett |
Fall 2002
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CS 263 Design of Programming Languages (Project Presentation) -- Prof. George Necula |
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CS 278 Machine Based Complexity Theory -- Prof. Luca Trevisan |
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CS 301 Teaching Techniques for Computer Science -- Prof. Mike Clancy |
Teaching (GSI)
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CS61A Structure and Interpretation of Computer Programs (Fall 2002) |
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CS188 Introduction to Artificial Intelligence (Spring 2003) |
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CS 281B/STAT 241B Advanced Topics in Learning and Decision Making (Spring 2006) |