
September 16th, 2008  Afshin Rostamizadeh, NYU
Sample Selection Bias Correction Theory
Abstract
Slides

September 23rd, 2008  Sanjiv Kumar, Google
Samplingbased 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, TelAviv
University and Google
Domain
Adaptation with Multiple Sources
Slides

November 11th, 2008  Ashish Rastogi, Google
Discussion: Does
Unlabeled Data Provably Help? Worstcase Analysis of the Sample
Complexity of SemiSupervised Learning, BenDavid et al. (COLT 2008)
Slides

November 18th, 2008  Afshin Rostamizadeh, NYU
Rademacher Bounds for Betamixing 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 PrivacyPreserving 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
PACBayes
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 KernelBased 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


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: Searchbased
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
KernelBased 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 Noni.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: LargeScale 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 LogLinear 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 Discriminativelytrained Finitestate
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
