Machine Learning Seminar Series
 
 
  Past Seminar Schedule
 

 

Machine Learning Lunchtime Chats

 

 
 
  Dec 19, 2007 Generalized Learning Factors Analysis: Improving Cognitive Models - Hao Cen, Ph.D. Candidate  
  Dec 12, 2007 Actively Learning Specific Function Properties with Applications to Statistical Inference - Brent Bryan, Ph.D. Candidate  
  Dec 05, 2007 Stacked Graphical Learning for Text Mining - Zhenzhen Kou, PhD Candidate  
  Oct 15, 2007 Towards Intelligent Assistance for a Data Mining Process - Abraham Bernstein, Professor  
  Sep 17, 2007 Machine Learning on Very Large Data Sets - Ivor Wai-Hung Tsang 
  May 16, 2007 Dynamics of Real-world Networks - Jurij Leskovec, Ph.D. Candidate  
  May 10, 2007 Measure Concentration of Strongly Mixing Processes with Applications - Leonid Kontorovich, Ph.D. Candidate  
  May 08, 2007 The Cluster-Squared Algorithm for Combining Economic Forecasts - Dan Li, Tepper PhD Student, ML MS Student  
  May 03, 2007 Learning Factors Analysis - A General Method for Cognitive Model - Hao Cen, Ph.D. Candidate  
  May 03, 2007 The Complexity of Interactive Machine Learning - Steve Hanneke, Ph.D. Candidate  
  May 02, 2007 A Comparison of Methods for Transductive Transfer Learning - Andrew Arnold, Ph.D. Candidate  
  Apr 27, 2007 Feature and Expert-based Market Prediction using Online Low-regret Algorithms - Chris Murray, MS Candidate  
  Apr 24, 2007 Learning Selectively Conditioned Forest Structures with Applications to DBNs and Classification - Brian Ziebart, PhD Candidate  
  Apr 24, 2007 Directions & Thesis Topics in Machine Learning - A Faculty Panel Discussion - Faculty Panel: Stephen Fienberg, Carlos Guestrin, Robert Murphy, Tom Mitchell (moderator) 
  Apr 12, 2007 Continuous Hidden Process Model for Time Series Expression Experiments - Yanxin Shi, LTI PhD Student, ML MS Student  
  Apr 10, 2007 Large-Scale Automated Analysis of Protein Subcellular Location Patterns in Randomly-Tagged 3T3 Cells - Juchang Hua, Biological Sciences PhD Student, ML MS Student  
  Apr 03, 2007 Detecting Anomalous Records in Large Categorical Datasets - Kaustav Das, Ph.D. Candidate  
  Apr 03, 2007 Modeling Networks using Kronecker Multiplication - Jurij Leskovec, PhD Candidate  
  Apr 02, 2007 Probabilistic Models of Human Learning - Charles Kemp, Ph.D. Candidate  
  Mar 01, 2007 The Discipline and Future of Machine Learning - Tom Mitchell, E. Fredkin Professor and Department Head, Machine Learning Dept.  
  Feb 27, 2007 Measure Concentration of Strongly Mixing Processes with Applications - Leonid Kontorovich, PhD Candidate  
  Feb 22, 2007 Sparse solutions to underdetermined linear systems - Joel Tropp, Assistant Professor  
  Feb 19, 2007 Hierarchical Dirichlet Processes for Modeling fMRI Brain Activation Patterns - Seyoung Kim, Graduate Student  
  Jan 29, 2007 Active Learning Search Strategies for Computing Level Sets: - Brent Bryan, PhD Candidate  
  Jan 10, 2007 Computational Methods for Analyzing and Modeling Gene Regulation Dynamics - Jason Ernst, PhD Candidate  
  Nov 20, 2006 Large Scale Detection of Irregularities in Accounting Data - David Steier, Center for Advanced Research
PricewaterhouseCoopers LLP 		 
  Oct 03, 2006 Learning-based Deformable Neuroimage Registration - Leonid Teverovskiy, PhD Candidate  
  Sep 28, 2006 Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words - Fei-Fei Li, Assistant Professor  
  Sep 26, 2006 Cost-sensitive Classifier Evaluation Using Cost Curves - Robert C. Holte, Professor  
  Aug 24, 2006 Intelligent Light Control Using Sensor Networks - Vipul Singhvi, Machine Learning MS Student  
  Jul 26, 2006 Dimensionality reduction and data fusion using diffusion geometries - Stephane Lafon 
  May 17, 2006 Approaches for Approximate Inference, Structure Learning and Computing Event Probability Bounds in Undirected Graphical Models - Pradeep Ravikumar, PhD Candidate  
  May 15, 2006 Stacked Graphical Learning - Zhenzhen Kou, PhD Candidate  
  May 08, 2006 How to Tell Some of the Bad Guys from Most of the Good Guys - Clark Glymour , Alumni University Professor, Carnegie Mellon University  
  May 04, 2006 Incremental Hierarchical Clustering of Text Documents - Nachiketa Sahoo, MS Candidate  
  May 02, 2006 Using Customer's Reported Forecasts to Predict Future Sales - Nihat Altintas, MS Candidate  
  Apr 27, 2006 Data Mining in Macroeconomic Data Sets - Ping Chen, KDD Masters Candidate  
  Apr 25, 2006 Dynamic Social Network Analysis using Latent Space Models - Purnamrita Sarkar, Ph.D. Candidate  
  Apr 12, 2006 A Bayesian Approach to Information Retrieval Using Sets of Items - Katherine A. Heller , Research Student, Gatsby Computational Neuroscience Unit  
  Apr 10, 2006 Tractable Learning of Structured Prediction Models - Ben Taskar, University of California at Berkeley  
  Apr 04, 2006 Active Learning for Identifying Function Threshold Boundaries - Brent Bryan, PhD Candidate  
  Apr 03, 2006 Calibration, Regret and Learning in Games - Rakesh Vohra, Northwestern University,  
  Mar 23, 2006 Topic Models for Social Network Analysis and Bibliometrics - Andrew McCallum, Associate Professor, University of Massachusetts Amherst  
  Feb 15, 2006 Support Vector Machines for Structured Outputs - Thorsten Joachims,, Professor, Department of Computer Science at Cornell University  
  Feb 09, 2006 All I Really Need to Know I Learned from Google - Oren Etzioni, Professor, University of Washington, Computer Science & Engineering  
  Dec 12, 2005 Learning for Semantic Parsing of Natural Language - Raymond J. Mooney, Professor  
  Dec 02, 2005 Finding Optimal Bayesian Networks by Dynamic Programming - Ajit Singh, PhD Candidate  
  Dec 01, 2005 Variational Inference and Learning for a Unified Model - Leonid Kontorovich, PhD Candidate  
  Nov 29, 2005 Automatic Filters for the Detection of Coherent Structure in Spatiotemporal Systems - Cosma Shalizi  
  Nov 21, 2005 Scalable Inference in Hierarchical Models of the Neocortex - Tom Dean 
  Nov 21, 2005 Learning to Estimate Query Difficulty - Elad Yom-Tov 
  Nov 17, 2005 *CANCELLED* A Fast Learning Algorithm for Deep Belief Nets - Geoffrey Hinton , Professor  
  Nov 14, 2005 Geometric tools for high-dimensional data analysis - Ann Lee 
  Sep 16, 2005 Experimental Complexity in Causal Discovery - Frederick Eberhardt, Masters Candidate  
  Sep 15, 2005 Contrastive Estimation for Unsupervised Sequence Modeling - Noah Smith, Center for Language and Speech Processing, Johns Hopkins University  
  Aug 24, 2005 Tutorial on non-parametric Bayesian methods for machine learning - Zoubin Ghahramani, Associate Research Professor  
  Jul 07, 2005 Automatic Discovery of Latent Variable Models - Ricardo Silva, PhD Candidate  
  Jul 06, 2005 Conditional Density Estimation using Finite Mixture Models with an Application to Astrophysics - Alex Rojas-Pena, CALD Masters Student  
  Jun 03, 2005 Tools for large Graph Mining - Deepayan Chakrabarti, PhD Candidate  
  Apr 07, 2005 Teaching Cyc to Fish - Michael Witbrock, Vice President for Research at Cycorp  
  Apr 04, 2005 Learning, Truth, and Simplicity: A New Explanation of Ockham's Razor - Kevin Kelly, Professor, Philosophy  
  Feb 09, 2005 A Finite Sample Upper Bound on the Generalization Error for Q-Learning - Susan Murphy, H.E. Robbins Professor of Statistics & Research Professor,  
  Feb 09, 2005 A Finite Sample Upper Bound on the Generalization Error for Q-Learning - Susan Murphy, H.E. Robbins Professor of Statistics & Research Professor,  
  Dec 10, 2004 Scalable class of graphical models for Social Networks - Anna Goldenberg, PhD Candidate  
  Dec 03, 2004 Generalizing the Hidden Markov Model - Anthony Brockwell, Assistant Professor, Statistics  
  Nov 12, 2004 Tools for Large Graph Mining - Deepayan Chakrabarti, PhD Candidate  
  Nov 04, 2004 Short Time Series Gene Expression Data - Jason Ernst, PhD Candidate  
  Nov 01, 2004 Interactive Discovery from Satellite Data - Yang Cai, Systems Scientist  
  Oct 13, 2004 Combining a Dictionary with a Hidden Markov Model for Protein Name Extraction - Zhenzhen Kou, PhD Candidate  
  Aug 05, 2004 Deformable Neuroimage Registration Using Interesting-Point and Feature Selection - Leonid Teverovskiy, PhD Candidate  
  May 20, 2004 A Hierarchical Graphical Model for Record Linkage - Pradeep Ravikumar, CALD PhD Candidate  
  Apr 23, 2004 The Berkeley BioText Project - Marti Hearst, Associate Professor, UC Berkeley  
  Mar 25, 2004 Multiagent Learning and Limited Agents - Michael A. Bowling, Assistant Professor of Computing Science at the University of Alberta  
  Mar 05, 2004 Online Customer Behavior: Measurement and Methodology - Andreas Weigend, Former Chief Scientist at Amazon.com  
  Feb 11, 2004 Non-Darwinian Evolutionary Computation: Guiding Evolution by Machine Learning - Ryszard S. Michalski 
  Feb 06, 2004 Is question answering an acquired skill? - Soumen Chakrabarti, Visiting Associate Professor, IIT Bombay  
  Feb 02, 2004 Budgeted Learning of Naive-Bayes Classifiers - Russ Greiner, Department of Computing Science and Alberta Ingenuity Centre for Machine Learning, University of Alberta  
  Dec 18, 2003 Learning Robust Rules from Data: the GenTree Algorithm - Yiheng Li 
  Dec 05, 2003 Large-Margin Methods for Natural Language Learning - Michael Collins, Assistant Professor, MIT  
  Dec 01, 2003 Rich Probabilistic Models for Genomic Data - Eran Segal, Stanford University  
  Sep 30, 2003 Educational data mining in a computer tutor that listens - Joseph Beck 
  Sep 25, 2003 Automatic Discovery of Latent Variable Models - Ricardo Silva 
  Aug 29, 2003 Improved Recognition of Protein Subcelluar Location Patterns via Feature Selection and Classifier Ensembles - Kai Huang 
  Aug 07, 2003 Advances in Network Tomography - Edoardo Airoldi 
  Aug 05, 2003 A computational approach to predict human sequence learning in reaction time experiments - Rainer Spiegel 
  Jun 19, 2003 Fractal Dimension for Data Mining - Krishna Kumarawamy 
  Jun 11, 2003 Introduction to *Modern* MDL - Peter Grunwald, CWI  
  Jun 02, 2003 Tools for Graph Mining - Yiping Zhan, CALD Masters Student  
  Jun 02, 2003 Tools for Graph Mining - Yiping Zhan 
  May 15, 2003 Using Machine Learning to Detect Cognitive States across Multiple - Xuerui Wang 
  May 12, 2003 People Tracking Using Many Simple Sensors - Daniel Wilson 
  Apr 22, 2003 Developing Information Extraction Resources for 100 Languages -Weakly Supervised Learning - Silviu Cucerzan, John Hopkins University  
  Apr 21, 2003 Propagation Algorithms for Probabilistic Inference in Graphical Models with Cycles - Max Welling, University of Toronto  
  Apr 18, 2003 Simultaneous localization and mapping using sparse extended - Yufeng Liu 
  Apr 16, 2003 Active Learning with Multiple Views - Ion Alexandru Muslea, University of California, Irvine  
  Apr 08, 2003 Unique Challenges of Learning Statistical Models of Relational Data - David Jensen, Director, Knowledge Discovery Laboratory, UMass  
  Jan 21, 2003 Mutli-agent Learning in Extensive Games with Complete Information - Pu Huang 
  Dec 18, 2002 Compromising Privacy with Trail Re-Identification: The REIDIT Algorithms - Bradley Malin 
  Oct 24, 2002 Mining computer tutor-student interaction data to assess students reading - Peng Jia, CALD Masters Student  
  Aug 19, 2002 Consumer Behavior Prediction using Parametric and Nonparametric Methods - Elena Eneva 
  Jul 25, 2002 Learning Rich Neural Network Topologies - Matteo Matteucci 
  Jun 13, 2002 Learning from Labeled and Unlabeled Data with Label Propagation - Xiaojin Zhu 
  May 17, 2002 Finding Motifs in Protein Structures: A Data Mining Approach - Marc Fasnacht 
  May 13, 2002 Object-based Image Modeling and Learning for Protein Subcellular Localization Patterns - Jie Yao 
  May 08, 2002 CANCELLED: DISCOVERING STRUCTURE IN HIGH-DIMENSIONAL DATA USING CONTRASTIVE BACKPROPAGATION - Geoffrey Hinton, Department of Computer Science, University of Toronto  
  May 06, 2002 The Structure of the Unobserved - Ricardo Silva 
  Apr 22, 2002 Large-scale Automated Forecasting using Fractals - Deepayan Chakrabarti 
  Apr 15, 2002 The "DGX" Distribution for Mining Massive, Skewed Data - Zhiqiang Bi 
  Mar 22, 2002 Diffusion Kernels on Graphs and Other Discrete Structures - Imre Kondor, CALD Masters Student  
  Feb 04, 2002 Boosting and Maximum Likelihood for Exponential Models - Guy Lebanon 
  Dec 17, 2001 Planning for Single and Multiple Actors in Markov Decision Processes with Deterministic Hidden State - Jamie Schulte, CALD Masters Student  
  Dec 03, 2001 Ockham's Razor Deduced from Error Minimization - Kevin Kelly, Associate Professor, Philosophy, Carnegie Mellon University  
  Sep 14, 2001 Analyzing grocery data for early detection of epidemics and bio-terrorism attacks - Anna Goldenberg, CALD Master's Student  
  May 17, 2001 Robust multi-scale image segmentation and clustering by maximum entropy methods - Joachim Buhmann, University of Bonn, Germany  
  May 09, 2001 Information Extraction with Finite State Models - Andrew McCallum, Vice President of Research & Development, WhizBang! Labs  
  May 07, 2001 Using Error-Correcting Codes for Efficient Text Categorization with a Large Number of Categories - Rayid Ghani 
  Mar 05, 2001 Organizational Learning and Adaptation: A Network Based Knowledge Management Approach - Kathleen Carley, Professor of Sociology & Organizations, SDS: Social & Decision Sciences  
  Jan 22, 2001 The Maximum-Margin Approach to Learning Text Classifiers - Methods, Theory & Algorithms - Thorsten Joachims, Post-doc, GMD  
  Dec 11, 2000 Markov Chain Monte Carlo Algorithms for Calculating Noninformative Bayesian Priors and Minimax Risk - John Lafferty, Associate Professor, CS, Carnegie Mellon  
  Dec 11, 2000 Markov Chain Monte Carlo Algorithms for Calculating Noninformative Bayesian Priors and Minimax Risk - John Lafferty, Associate Professor  
  Dec 04, 2000 Expectation Propagation for Approximate Bayesian Inference - Tom Minka 
  Dec 04, 2000 Bayesian Learning of Model Structure - Zoubin Ghahramani, University College London  
  Dec 04, 2000 Bayesian Learning of Model Structure - Zoubin Ghahramani 
  Dec 04, 2000 Expectation Propagation for Approximate Bayesian Inference - Tom Minka 
  Oct 02, 2000 Extracting information from the Web for Concept Learning and Collaborative Filtering - William Cohen, Distinguished Research Scientist, WhizBang! Labs  
  Oct 02, 2000 Extracting information from the Web for Concept Learning and Collaborative Filtering - William Cohen 
  Sep 18, 2000 Parallel Experiment Planning, Macromolecular Crystallization and Computational Biology - Vanathi Gopalakrishnan, Visiting Assistant Professor  
  May 24, 2000 Challenges in Performance Management: Applications and Problems for Machine Intelligence and Visualization - Joseph L. Hellerstein 
  Mar 20, 2000 The Aqua Approximate Query Answering System - Phil Gibbons, Visiting Professor Department of Computer Science  
  Jan 31, 2000 The Open Mind Initiative: A collaborative framework for collecting and learning netizen contributions to open source 'intelligent' software - David Stork, Chief Scientist of Ricoh Silicon Valley and Consulting Associate Professor of Electrical Engineering at Stanford University  
  Jan 31, 2000 The Open Mind Initiative: A collaborative framework for collecting and learning netizen contributions to open source 'intelligent' software - David Stork, Chief Scientist of Ricoh Silicon Valley and Consulting Associate Porfessor of Electical Engineering at Stanford University  
  Dec 02, 1999 Automatic Data Analysis using Model Based Priors for Marketing Datasets - Alan Montgomery 
  Nov 18, 1999 Collaborative Nets - Sarosh Talukdar 
  Nov 05, 1999 Data Mining Software Demonstrations - Peter Spirtes 
  Oct 21, 1999 New Approaches to Two Tasks of Knowledge Discovery: Niche Finding (new) and Benchmarking (old) - Raul Valdes-Perez 
  Mar 18, 1999 The Mellon Blitz Project: Predicting and Causing Checking Account Attrition - Richard Scheines & Peter Spirtes 
  Feb 18, 1999 Tractable structure search in the presence of latent variables - Thomas Richardson, Associate Professor of Statistics  
 
View Current Seminars