External Talks/Visits

2005

• June 14, 2005
  Edinburgh, Informatics

• June 7, 2005
  Inference Group, Cavendish Labs, Cambridge UK

• May 25, 2005
  Gatsby Computational Neuroscience Unit, UCL, UK

• April 26, 2005
  CIAR NCAP Workshop on Manifold Learning and Dimensionality Reduction, Montreal

• April 18, 2005
  Toyota Technological Institute at Chicago

• March 29, 2005
  Learning, Language, Vision and Graphics Colloquium, MIT CSAIL

• March 11, 2005
  Spoken Language Systems Group, MIT CSAIL

• March 4, 2005
  Boston University Hearing Research Center

• Feb 24, 2005
  Machine Learning Lunch, U.Mass Amherst

• Feb 23, 2005
  CMPSCI 791 BB, U.Mass. Amherst

• Feb 22, 2005
  6.881 MIT

• Feb 16,, 2005
  Stochastic Systems Group, MIT

• Jan 23-28, 2005
  Machine Learning Summer School, 2005, Canberra

• Jan 27, 2005
  Australian Centre for Field Robotics, Sydney

  2004

• December 10, 2004
  MSRI High Dimensional Data Workshop, Berkeley

• November 8, 2004
  Caltech CNSE NSF Site Visit

• October 22, 2004
  Artificial Intelligence in Medicince Retreat

• October 18, 2004
  University of Chicago, Dept. Statistics

• September 8, 2004
  Proteomics and Bioinformatics Program Retreat

• August 23, 2004
  Hanse Institute for Advance Study Hearing Workshop, Germany

• July 28, 2004
  Google Labs, NYC

• July26, 2004
  NYU CCPP

• June 8, 2004
  IRIS Learning Workshop, Ottawa

• May 2004
  Microsoft Research, Redmond

• May 2004
  University of Washington, Seattle

• April 2004
  Department of Computer Science, U.Mass Amherst

• March 2004
  CSLP JHU

• March 2004
  UBC

  2003

• November 2003
  MITACS

• November 2003
  NSF Workshop

• September 2003
  Hamilton Institute

• September 2003
  Eurospeech

• August 2003
  NYU

• July 2003
  University of Waterloo

• June 29, 2003
  Scandinavian Conference on Image Analysis (SCIA'03)
  Invited Tutorial, Hidden Markov Models

• June 24, 2003
  Gatsby Unit, London
  Training Gaussian Processes with Noisy Inputs

• June 23, 2003
  Inference Group, Cambridge University
  Learning from single and multiple sequences on manifolds

• June 9, 2003
  Advances in Machine Learning, Montreal
  Invited Presentation, Learning from Sequences on Manifolds

• Feb. 17-21, 2003
  NYU Physics
  

• January 31, 2003
  Overture Research
  Simultaneous Clustering of Rows and Columns

  2002

• December 6, 2002
  Stanford CS
  

• December 5, 2002
  Machine Learning Group, Google
  Learning Compact Approximations of Large Matrices

• November 25, 2002
  LISA Group, U. Montreal
  Learning Compact Approximations of Large Matrices

• July 3, 2002
  Jordan Group, Berkeley CS/Stats
  Stochastic Neighbor Emebdding

• May 14, 2002
  CALD/Machine Learning, CMU
  Greedy Neighbour Clustering

  2001

• December 7, 2001
  Geometric Methods in Learning workshop, NIPS'01.

• October 15, 2001
  LISA Group, U. Montreal
  Nonlinear Dimensionality Reduction

• October, 2001
  Intelligent Hearing Aids, Niagara on the Lake
  Invited Presentation, One Microphone Separation Methods

• May 14, 2001
  Seung Lab, MIT
  Representations of Images for Learning

• April 26, 2001
  MERL, Cambridge
  Weight Decay for Images

• April 10/20,2001
  Stanford CS
  Learning Nonlinear Data Manifolds

• April 5/6,2001
  Caltech CS
  Learning Nonlinear Data Manifolds

• April 3/4,2001
  UW Seattle CSE
  Learning Nonlinear Data Manifolds

• March 16,2001
  KCL Signal Processing Seminar Series
  One Microphone Source Separation

• March 7/8,2001
  MIT EECS
  Learning Nonlinear Data Manifolds

• March 13,21,23,2001
  GCNU Internal Tutorial
  Basics of Control Theory

• Feb.5/6 ,2001
  Microsoft Research Redmond
  Scalable Learning of Nonlinear Manifolds from Data

• January 30,2001
  U.Toronto
  Learning Nonlinear Data Manifolds

• January 24,2001
  CMU
  Learning of Nonlinear Manifolds from Data

• January 23,2001
  Whizbang Labs, Pittsburgh
  Nonlinear Semantic Analysis

• January 15,2001
  Informatics, Edinburgh
  Locally Linear Embedding

  2000

• December 11,2000
  Microsoft Research, Cambridge
  Scalable Learning of Nonlinear Manifolds from Data

• November 28, 2000
  Advances in Neural Information Processing Systems 13 (NIPS'00)
  Oral Presentation, One Microphone Source Separation

• September 10, 2000
  Banbury Center Meeting
  Unsupervised Learning of Nonlinear Manifolds

• October23/24,2000
  ATT Labs Research -- Florham Park/Newmann Springs
  Scalable Learning of Nonlinear Manifolds from Data

• October 20,2000
  Bell Labs, Lucent Technologies
  Unsupervised Learning of Nonlinear Manifolds

• October16 ,2000
  Frey Lab, U.Waterloo
  Locally Linear Embedding

• June27, 2000
  Hearnet2 Meeting, Brighton UK
  HMM Model Combination for Auditory Scene Analysis

• April 14, 2000
  Snowbird Learning Workshop
  One Microphone Source Separation

• April 10, 2000
  Rank Prize Meeting
  One Microphone Source Separation

• March 10, 2000
  Seung Lab, BCS, MIT
  Tutorial on Exact Sampling

• February 11, 2000
  Inference Group (Mackay), Cambridge University
  Tutorials on Exact Sampling and IPF/GIS

• January 21, 2000
  Informatics, Edinburgh University
  Constrained HMMs and Applications

• January 20, 2000
  CSTR, Edinburgh University
  Articulatory Speech Processing

• January 13, 2000
  Kernel Day, Microsoft Research, Cambridge
  Dynamical Systems in Kernel Space

  1999

• November 29, 1999
  NIPS Tutorial on Unsupervised Learning with Zoubin Ghahramani.
  (The tutorial slides are now available on my notes page.)

• September 9, 1999
  University of Waterloo, CS Dept.
  Constrained Hidden Markov Models for Sequence Analysis

• September 1, 1999
  Gatsby Unit Neural computation tutorial, on Hidden Markov Models and Linear Dynamical Systems. (link).
  (The slides from my lectures on are available on my notes page.)

• June 17, 1999
  Gatsby Unit Annual Symposium
  Learning Global Coordinates for Perceptual Data

• February 26, 1999
  Washington University, St. Louis EE Dept.
  Self-Organizing Hidden Markov Models: Learning Low Dimensional Maps to Explain Sequences of High Dimensional Data (link)

• February 25, 1999
  University of Washington, Seattle CS/EE Dept.
  EM Algorithms for PCA and SPCA

• February 4, 1999
  ATT Research Labs, Florham Park NJ
  Articulatory Constrains for Speech Recognition

• January 22, 1999
  JPL Machine Learning Group, Pasadena CA
  Self-Organizing Hidden Markov Models: Learning Low Dimensional Maps to Explain Sequences of High Dimensional Data (link)

• January 13, 1999
  Thesis Defense, California Institute of Technology
  Articulatory Speech Processing
  Here are the slides from my thesis talk. There is also an online version of the thesis defense with the slides and some comments.
  Talk abstract. A postscript copy of the talk poster.

  1998

• October 30, 1998
  Princeton University Program in Applied and Computational Mathematics
  Dynamical Systems and Nonlinear Science Seminar
  Learning Low-Dimensional Maps to Explain High-Dimensional Sequences of Data

• October 9, 1998
  University of British Columbia, CICRS/CS
  Machines that Talk and Listen: Speech Processing by Humans and Machine (link,abstract)

• June 8, 1998
  Microsoft Research, Redmond
  EM algorithms for PCA and SPCA and
  Using speech production models in speech processing

• June 5, 1998
  University of California, Irvine ICS Dept.
  EM Algorithms for PCA and SPCA (link)

• June 1, 1998
  UCLA, Dept. Linguistics
  Regularities in articulatory data

• May 26, 1998
  TRW Speech Group, Domingos Hills CA
  State of the art and new opportunities in speech processing

• May 27, 1998
  Interval Research, Palo Alto CA
  Can you hear the shape of the mouth? Using speech production models in speech processing (link)

• May 18, 1998
  Caltech Distinguished Graduate Student Lecture (Everhart Lecture Series)
  Machines that Talk and Listen: Speech Processing by Humans and Machines (link)
  A scanned version of the talk poster (thanks to my dad).
  Talk abstract.
  

• May 1, 1998
  Sarnoff Research Labs, Princeton NJ
  Can you hear the shape of the mouth? Using speech production models in speech processing

• April 6, 1998
  Bell Labs (Lucent), Murray Hill NJ
  Towards Articulatory Speech Recognition

• February 12, 1998
  University of Toronto, Dept. Computer Science
  Workshop on Computational Neuroscience and Generative Models
  Speech Processing: Impossible Problem or Low Hanging Fruit?

  1997 and before

• October 23, 1997
  Lawrence Livermore National Labs
  Extra-Acoustic Information in Speech Processing

• October 15, 1997
  EE Systems Seminar, Caltech
  A Unification of Popular Linear Gaussian Models

• July1/2 1997
  Bell Labs (Lucent), Murray Hill NJ
  Towards articulatory speech processing

• August 29, 1996
  University of Waterloo, EE Dept.
  Experiments in Articulatory Speech Recognition

• August 12, 1996
  Workshop '96, CLSP, Johns Hopkins University
  Initial Experiments in Articulatory Speech Recognition (link)

• June 6 1996
  DIMACS2 Conference on DNA Computing, Princeton NJ
  A Sticker Based Model for DNA Computation
  Here are the slides from this talk which I gave at DIMACS2 in Princeton.
  [version of june'96--> tar.gz(914K)]
  

• May 21, 1996
  Engineering Research Council Industry Conference, Caltech
  Initial Experiments in Articulatory Speech Recognition

• March 18, 1996
  JPL Machine Learning Group
  Support Vector Machines and the VC Dimension (link)

Sam Roweis, Machine Learning Group, Toronto Computer Science, www.cs.toronto.edu/~roweis