Gatsby Unit Seminar Series

Usual time: Thursday, 16:00 - 17:00
Location (unless otherwise noted): B10, Alexandra House
iCalendar URL: www.csml.ac.uk/ics/series/1

Upcoming Events

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Previous Events

DateDescription
Wed, 12 Oct 2016 Clayton Scott (University of Michigan): External Seminar Clayton Scott
Mon, 03 Oct 2016 Lester Mackey (Stanford University): External Seminar Lester Mackey
Wed, 21 Sep 2016 Richard Wilkinson (The University of Sheffield): External Seminar Talk by Richard Wilkinson
Wed, 07 Sep 2016 Hanna Wallach (Microsoft Research New York City): External Seminar Talk by Hanna Wallach
Wed, 27 Jul 2016 Daniel Hsu (Columbia University): External Seminar: Daniel Hsu
Wed, 20 Jul 2016 Amir Globerson (Tel Aviv University): External Seminar Amir Globerson
Tue, 05 Jul 2016 Sanmi Koyejo (Stanford University and University of Illinois): External Seminar Talk by Sanmi Koyejo
Mon, 16 May 2016 Piotr Indyk MIT (MIT): External Talk by Piotr Indyk
Mon, 21 Mar 2016 Joan Bruna (Berkeley USA): External Talk by Joan Bruna
Wed, 09 Mar 2016 Paul Fearnhead (Lancaster University): External Talk by Paul Fearnhead
Wed, 02 Mar 2016 Kamalika Chaudhuri (University of California): Seminar: External Talk by Kamalika Chaudhuri
Wed, 24 Feb 2016 Eric Moulines (LTCI (TELECOM ParisTech, CNRS)): External Talk by Eric Moulines
Tue, 26 Jan 2016 Julien Mairal (INRIA): External Talk by Julien Mairal
Wed, 13 Jan 2016 Lorenzo Rosasco (MIT/IIT): External Seminar: Lorenzo Rosasco
Tue, 05 Jan 2016 Pradeep Ravikumar (Department of Computer Science, University of Texas, Austin): External Seminar: Pradeep Ravikumar
Wed, 16 Dec 2015 Tamara Broderick (MIT): External Talk: Tamara Broderick
Tue, 10 Nov 2015 Csaba Szepesvari (University of Alberta): (Bandit) Convex Optimization with Biased Noisy Gradient Oracles
Wed, 04 Nov 2015 Gilles Blanchard (Universität Potsdam): Convergence rates of for spectral regularization methods for statistical inverse learning problems
Mon, 02 Nov 2015 Patricia Reynaud-Bouret (Laboratoire J. A. Dieudonné): Estimation of local independence graphs via Hawkes processes to unravel functional neuronal connecti
Wed, 15 Apr 2015 Max Welling: Bayesian Inference in Complex Generative Models
Wed, 11 Feb 2015 Anthony Lee: Perfect simulation using atomic regeneration with application to Sequential Monte Carlo
Wed, 28 Jan 2015 Jonas Peters (Caltech): Causal Inference using Invariant Prediction
Wed, 20 Feb 2013 Zoubin Ghahramani (University of Cambridge): Bayesian nonparametric modelling of networks
Wed, 30 Jan 2013 Neil Lawrence (University of Sheffield): Deep Gaussian Processes
Wed, 28 Nov 2012 Charles Sutton (University of Edinburgh): Quasi-Newton Methods and Continuous Relaxations for MCMC
Wed, 14 Nov 2012 Wicher Bergsma (LSE): Nonparametric testing of conditional independence
Wed, 31 Oct 2012 Roger Grosse (MIT): Model selection in a large compositional space
Tue, 03 Jul 2012 Inderjit S. Dhillon (The University of Texas at Austin): Fast Coordinate Descent Methods with Variable Selection for Non-negative Matrix Factorization
Mon, 02 Jul 2012 Yoshua Bengio (University of Montreal): Sampling from Auto-Encoders performing Manifold Learning and Implicit Density Estimation
Fri, 22 Jun 2012 Steven C.H. Hoi (Nanyang Technological University): Online Learning for Mining Big Media Data
Wed, 23 May 2012 Marc Toussaint (FU Berlin): Optimal control and model-free Reinforcement Learning as KL minimization
Wed, 11 Apr 2012 Bert Kappen (Radboud University Nijmegen): Path Integral Reinforcement Learning
Mon, 02 Apr 2012 Zaid Harchaoui (INRIA Rhone-Alpes): Learning with matrix gauge regularization penalty
Wed, 14 Mar 2012 Iain Murray (University of Edinburgh): Sampling hierarchical latent Gaussian models
Mon, 12 Mar 2012 Lorenzo Rosasco (Massachusetts Institute of Technology and Istituto Italiano di Tecnologia): Learning Functions and (Data) Sets with Spectral Regularization
Wed, 29 Feb 2012 Sumeettpal Singh (University of Cambridge): Parameter Estimation for Hidden Markov Models with Intractable Likelihoods
Wed, 22 Feb 2012 Vikash Mansinghka (MIT): How to be stochastic about probabilistic programming, and why it is worth the trouble
Wed, 15 Feb 2012 Danny Bickson (Carnegie Mellon University): Large scale iterative computation using GraphLab