Machine Learning Ph.D. Seminar

2008-2009 Schedule

September 16th, 2008 - Afshin Rostamizadeh, NYU
Sample Selection Bias Correction Theory
Abstract Slides
September 23rd, 2008 - Sanjiv Kumar, Google
Sampling-based Approximate SVD
Abstract
September 30th, 2008 - No seminar
October 7th, 2008 - Ameet Talwalkar, NYU
Discussion: On the Margin Explanation of Boosting Algorithms, Wang et al. (COLT 2008)
Slides
October 14th, 2008 - Academic holiday, no seminar
October 21st, 2008 - Eugene Weinstein, NYU
Introduction to Topic Models
Abstract Slides
October 28th, 2008 - No seminar
November 7th, 2008, 11:30am, WWH 1302 (special session: please note unusual time and location) - Yishay Mansour, Tel-Aviv University and Google
Domain Adaptation with Multiple Sources
Slides
November 11th, 2008 - Ashish Rastogi, Google
Discussion: Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning, Ben-David et al. (COLT 2008)
Slides
November 18th, 2008 - Afshin Rostamizadeh, NYU
Rademacher Bounds for Beta-mixing Distributions
Abstract Slides
November 25th, 2008 - No seminar
December 2nd, 2008 - Rob Fergus, NYU
Spectral Hashing
Abstract
January 20th, 2009 - Umar Syed, Princeton University
Hybrid Supervised/Reinforcement Learning Problems
Abstract Slides
January 27th, 2009 - No seminar
February 3rd, 2009 - Special joint session with the Cryptography Reading Group
Claire Monteleoni, Columbia University
Advances in Privacy-Preserving Machine Learning
Abstract Slides
February 10th, 2009 - Ameet Talwalkar, NYU
Discussion: Spectral Clustering with Perturbed Data, Huang et al. (NIPS 2008)
February 17th, 2009 - John Langford, Yahoo
PAC-Bayes
Tutorial Link Slides
February 24th, 2009 - Seminar canceled
March 3rd, 2009 - Eugene Weinstein, NYU
Discussion: Support Vector Method for Novelty Detection (Scholkopf et al., NIPS 2000)
Slides
March 10th, 2009 - No seminar
March 17th, 2009 - Spring break, no seminar
March 24th, 2009 - Afshin Rostamizadeh, NYU
Overview on Canonical Correlation Analysis
Paper Link
March 31st, 2009 - Ameet Talwalkar, NYU
Logistic Regression, Kernel Logistic Regression and Import Vector Machines
Paper Link
April 7th, 2009 - Aryeh Kontorovich, Weizmann Institute
Universal Kernel-Based Learning with Applications to Regular Languages
Abstract
April 14th, 2009 - No seminar
April 21st, 2009 - Spencer Greenberg, NYU
Occam' s Razor : Understanding the Cost of Complexity
Abstract

2007-2008 Schedule

September 4th, 2007 - Mehryar Mohri
Introduction to Rademacher Complexity (Part I)
Slides
September 11th, 2007 - Mehryar Mohri
Introduction to Rademacher Complexity (Part II)
Slides
September 18th, 2007 - No seminar
September 25th, 2007 - Ashish Rastogi
Title: McDiarmid's Inequality and its Applications
Abstract Slides
October 2nd, 2007 - Eugene Weinstein
Discussion: Search-based Structured Prediction, by Hal Daume, John Langford, and Daniel Marcu (submitted to Machine Learning)
Slides
October 9th, 2007 - Afshin Rostamizadeh
Discussion: Learning the Kernel Matrix with Semidefinite Programming, Lanckriet et al. (JMLR 2004)
Slides
October 16th, 2007 - Cyril Allauzen
Discussion: On Optimal Learning Algorithms for Multiplicity Automata, L. Bisht, N. Bshouty and H. Mazzawi (COLT 2006)
Slides
October 23rd, 2007 - No seminar
October 30th, 2007 - Ameet Talwalkar
Discussion: On the Nystrom Method for Approximating a Gram Matrix for Improved Kernel-Based Learning, Petros Drineas and Michael Mahoney (JMLR 2005).
Slides
November 6th, 2007 - Yishay Mansour
Reinforcement Learning, Part 1
Abstract   Slides   Class Notes
November 13th, 2007 - Yishay Mansour
Reinforcement Learning, Part 2
Abstract
November 20th, 2007 - No seminar
November 27th, 2007 - Afshin Rostamizadeh
Stability Bounds for Non-i.i.d. Processes
Paper Link
December 4th, 2007 - No seminar
December 11th, 2007 (NOTE ROOM CHANGE: WWH 1013) - Boulos Harb
Sampling Algorithms for Lp Regression and an Application to Feature Selection
Paper Links: Sampling Algorithms and Coresets for Lp Regression (SODA 2008), Feature Selection Methods for Text Classification (KDD 2007)
January 22nd, 2008 - Ameet Talwalkar
Title: Large-Scale Manifold Learning
Abstract
January 29th, 2008 - No seminar
Feburary 5th, 2008 - Afshin Rostamizadeh
Discussion: Learning Bounds for Domain Adaptation, Blitzer et al. (NIPS 2007)
Slides
February 12th, 2008 - Subhash Khot
Title: Hardness Results for Some Learning Problems
Abstract
February 19th, 2008 - Eugene Weinstein
Discussion: Discriminative Log-Linear Grammars with Latent Variables, Petrov and Klein (NIPS 2007)
Slides
February 26th, 2008 - Ashish Rastogi
Discussion: FilterBoost: Regression and Classification on Large Datasets, Bradley and Schapire (NIPS 2007)
Slides
March 4th, 2008 - no seminar
March 11th, 2008 - Rob Fergus
Title: Large image databases and small codes for object recognition
Abstract
Slides
March 18th, 2008 - Spring Break, no seminar
March 25th, 2008 - Sanjoy Dasgupta
Title: Random projection trees and low dimensional manifolds
Abstract
April 1st, 2008 - Afshin Rostamizadeh
Discussion: A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance and An Introduction to Conditional Random Fields for Relational Learning
April 8th, 2008 - Ameet Talwalkar
Discussion: Dimension Reduction Using Stable Random Projections
April 15th, 2008 - Risi Kondor
The skew spectrum of graphs --- a new class of graph invariants
Abstract
Slides
April 22nd, 2008 - Eugene Weinstein
Discussion: Discriminative Training of Decoding Graphs for Large Vocabulary Continuous Speech Recognition (Kuo, Kingsbury, Zweig, ICASSP 2007)
Slides
April 30th, 2008 - Ashish Rastogi
Special session: thesis defense

Details

  • Location: Warren Weaver Hall (251 Mercer Street), Room 1314 (unless otherwise noted)
  • Time: Tuesdays 1:45-3:45pm (unless otherwise noted)
  • Please subscribe to the mailing list for the seminar.