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Author Information
Csaba Szepesvari (University of Alberta)
Isabelle Guyon (U. Paris-Saclay & ChaLearn)
Isabelle Guyon recently joined Google Brain as a research scientist. She is also professor of artificial intelligence at Université Paris-Saclay (Orsay). Her areas of expertise include computer vision, bioinformatics, and power systems. She is best known for being a co-inventor of Support Vector Machines. Her recent interests are in automated machine learning, meta-learning, and data-centric AI. She has been a strong promoter of challenges and benchmarks, and is president of ChaLearn, a non-profit dedicated to organizing machine learning challenges. She is community lead of Codalab competitions, a challenge platform used both in academia and industry. She co-organized the “Challenges in Machine Learning Workshop” @ NeurIPS between 2014 and 2019, launched the "NeurIPS challenge track" in 2017 while she was general chair, and pushed the creation of the "NeurIPS datasets and benchmark track" in 2021, as a NeurIPS board member.
Nicolai Meinshausen (ETH Zurich)
David Blei (Columbia University)
David Blei is a Professor of Statistics and Computer Science at Columbia University, and a member of the Columbia Data Science Institute. His research is in statistical machine learning, involving probabilistic topic models, Bayesian nonparametric methods, and approximate posterior inference algorithms for massive data. He works on a variety of applications, including text, images, music, social networks, user behavior, and scientific data. David has received several awards for his research, including a Sloan Fellowship (2010), Office of Naval Research Young Investigator Award (2011), Presidential Early Career Award for Scientists and Engineers (2011), Blavatnik Faculty Award (2013), and ACM-Infosys Foundation Award (2013). He is a fellow of the ACM.
Elias Bareinboim (Purdue)
Bernhard Schölkopf (MPI for Intelligent Systems)
Bernhard Scholkopf received degrees in mathematics (London) and physics (Tubingen), and a doctorate in computer science from the Technical University Berlin. He has researched at AT&T Bell Labs, at GMD FIRST, Berlin, at the Australian National University, Canberra, and at Microsoft Research Cambridge (UK). In 2001, he was appointed scientific member of the Max Planck Society and director at the MPI for Biological Cybernetics; in 2010 he founded the Max Planck Institute for Intelligent Systems. For further information, see www.kyb.tuebingen.mpg.de/~bs.
Pietro Perona (California Institute of Technology)
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Ethan Harris · Tom White · Oh Hyeon Choung · Takashi Shinozaki · Dipan Pal · Katherine L. Hermann · Judy Borowski · Camilo Fosco · Chaz Firestone · Vijay Veerabadran · Benjamin Lahner · Chaitanya Ryali · Fenil Doshi · Pulkit Singh · Sharon Zhou · Michel Besserve · Michael Chang · Anelise Newman · Mahesan Niranjan · Jonathon Hare · Daniela Mihai · Marios Savvides · Simon Kornblith · Christina M Funke · Aude Oliva · Virginia de Sa · Dmitry Krotov · Colin Conwell · George Alvarez · Alex Kolchinski · Shengjia Zhao · Mitchell Gordon · Michael Bernstein · Stefano Ermon · Arash Mehrjou · Bernhard Schölkopf · John Co-Reyes · Michael Janner · Jiajun Wu · Josh Tenenbaum · Sergey Levine · Yalda Mohsenzadeh · Zhenglong Zhou -
2019 : Welcome and Opening Remarks »
Adrienne Mendrik · Wei-Wei Tu · Isabelle Guyon · Evelyne Viegas · Ming LI -
2019 Poster: On the Fairness of Disentangled Representations »
Francesco Locatello · Gabriele Abbati · Thomas Rainforth · Stefan Bauer · Bernhard Schölkopf · Olivier Bachem -
2019 Poster: On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset »
Muhammad Waleed Gondal · Manuel Wuethrich · Djordje Miladinovic · Francesco Locatello · Martin Breidt · Valentin Volchkov · Joel Akpo · Olivier Bachem · Bernhard Schölkopf · Stefan Bauer -
2019 Poster: Think out of the "Box": Generically-Constrained Asynchronous Composite Optimization and Hedging »
Pooria Joulani · András György · Csaba Szepesvari -
2019 Poster: Detecting Overfitting via Adversarial Examples »
Roman Werpachowski · András György · Csaba Szepesvari -
2019 Poster: Teaching Multiple Concepts to a Forgetful Learner »
Anette Hunziker · Yuxin Chen · Oisin Mac Aodha · Manuel Gomez Rodriguez · Andreas Krause · Pietro Perona · Yisong Yue · Adish Singla -
2019 Poster: Perceiving the arrow of time in autoregressive motion »
Kristof Meding · Dominik Janzing · Bernhard Schölkopf · Felix A. Wichmann -
2019 Poster: Poisson-Randomized Gamma Dynamical Systems »
Aaron Schein · Scott Linderman · Mingyuan Zhou · David Blei · Hanna Wallach -
2019 Poster: Selecting causal brain features with a single conditional independence test per feature »
Atalanti Mastakouri · Bernhard Schölkopf · Dominik Janzing -
2019 Poster: Variational Bayes under Model Misspecification »
Yixin Wang · David Blei -
2019 Poster: Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes »
Junzhe Zhang · Elias Bareinboim -
2019 Poster: Using Embeddings to Correct for Unobserved Confounding in Networks »
Victor Veitch · Yixin Wang · David Blei -
2019 Poster: Kernel Stein Tests for Multiple Model Comparison »
Jen Ning Lim · Makoto Yamada · Bernhard Schölkopf · Wittawat Jitkrittum -
2019 Poster: Adapting Neural Networks for the Estimation of Treatment Effects »
Claudia Shi · David Blei · Victor Veitch -
2019 Poster: Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets »
Daniel Kumor · Bryant Chen · Elias Bareinboim -
2019 Poster: Characterization and Learning of Causal Graphs with Latent Variables from Soft Interventions »
Murat Kocaoglu · Amin Jaber · Karthikeyan Shanmugam · Elias Bareinboim -
2019 Poster: Identification of Conditional Causal Effects under Markov Equivalence »
Amin Jaber · Jiji Zhang · Elias Bareinboim -
2019 Spotlight: Perceiving the arrow of time in autoregressive motion »
Kristof Meding · Dominik Janzing · Bernhard Schölkopf · Felix A. Wichmann -
2019 Spotlight: Identification of Conditional Causal Effects under Markov Equivalence »
Amin Jaber · Jiji Zhang · Elias Bareinboim -
2018 : Afternoon Welcome - Isabelle Guyon and Evelyne Viegas »
Isabelle Guyon -
2018 Workshop: CiML 2018 - Machine Learning competitions "in the wild": Playing in the real world or in real time »
Isabelle Guyon · Evelyne Viegas · Sergio Escalera · Jacob D Abernethy -
2018 : Model-free vs. Model-based Learning in a Causal World: Some Stories from Online Learning to Rank »
Csaba Szepesvari -
2018 : Causality and Distributional Robustness »
Nicolai Meinshausen -
2018 : AutoML3 - LifeLong ML with concept drift Challenge: Overview and award ceremony »
Hugo Jair Escalante · Isabelle Guyon · Daniel Silver · Evelyne Viegas · Wei-Wei Tu -
2018 : The Blessings of Multiple Causes »
David Blei -
2018 : Evaluating Causation Coefficients »
Isabelle Guyon -
2018 : Causality and Transfer Learning »
Elias Bareinboim -
2018 : From Micro-Variables to Macro-Causes »
Pietro Perona -
2018 : Learning Independent Mechanisms »
Bernhard Schölkopf -
2018 Poster: Informative Features for Model Comparison »
Wittawat Jitkrittum · Heishiro Kanagawa · Patsorn Sangkloy · James Hays · Bernhard Schölkopf · Arthur Gretton -
2018 Poster: Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners »
Yuxin Chen · Adish Singla · Oisin Mac Aodha · Pietro Perona · Yisong Yue -
2018 Poster: TopRank: A practical algorithm for online stochastic ranking »
Tor Lattimore · Branislav Kveton · Shuai Li · Csaba Szepesvari -
2018 Poster: Structural Causal Bandits: Where to Intervene? »
Sanghack Lee · Elias Bareinboim -
2018 Poster: Equality of Opportunity in Classification: A Causal Approach »
Junzhe Zhang · Elias Bareinboim -
2018 Poster: Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models »
Alexander Neitz · Giambattista Parascandolo · Stefan Bauer · Bernhard Schölkopf -
2018 Poster: PAC-Bayes bounds for stable algorithms with instance-dependent priors »
Omar Rivasplata · Emilio Parrado-Hernandez · John Shawe-Taylor · Shiliang Sun · Csaba Szepesvari -
2017 : Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation »
Alice Oh · Bernhard Schölkopf -
2017 Workshop: Machine Learning Challenges as a Research Tool »
Isabelle Guyon · Evelyne Viegas · Sergio Escalera · Jacob D Abernethy -
2017 : Introduction - Isabelle Guyon and Evelyne Viegas »
Isabelle Guyon -
2017 : Panel: On the Foundations and Future of Approximate Inference »
David Blei · Zoubin Ghahramani · Katherine Heller · Tim Salimans · Max Welling · Matthew D. Hoffman -
2017 Workshop: Advances in Approximate Bayesian Inference »
Francisco Ruiz · Stephan Mandt · Cheng Zhang · James McInerney · James McInerney · Dustin Tran · Dustin Tran · David Blei · Max Welling · Tamara Broderick · Michalis Titsias -
2017 Poster: Avoiding Discrimination through Causal Reasoning »
Niki Kilbertus · Mateo Rojas Carulla · Giambattista Parascandolo · Moritz Hardt · Dominik Janzing · Bernhard Schölkopf -
2017 Poster: Hierarchical Implicit Models and Likelihood-Free Variational Inference »
Dustin Tran · Rajesh Ranganath · David Blei -
2017 Poster: Experimental Design for Learning Causal Graphs with Latent Variables »
Murat Kocaoglu · Karthikeyan Shanmugam · Elias Bareinboim -
2017 Poster: Multi-view Matrix Factorization for Linear Dynamical System Estimation »
Mahdi Karami · Martha White · Dale Schuurmans · Csaba Szepesvari -
2017 Poster: Structured Embedding Models for Grouped Data »
Maja Rudolph · Francisco Ruiz · Susan Athey · David Blei -
2017 Poster: Variational Inference via $\chi$ Upper Bound Minimization »
Adji Bousso Dieng · Dustin Tran · Rajesh Ranganath · John Paisley · David Blei -
2017 Poster: Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning »
Shixiang (Shane) Gu · Timothy Lillicrap · Richard Turner · Zoubin Ghahramani · Bernhard Schölkopf · Sergey Levine -
2017 Poster: Context Selection for Embedding Models »
Liping Liu · Francisco Ruiz · Susan Athey · David Blei -
2017 Poster: AdaGAN: Boosting Generative Models »
Ilya Tolstikhin · Sylvain Gelly · Olivier Bousquet · Carl-Johann SIMON-GABRIEL · Bernhard Schölkopf -
2016 : Causal Inference for Recommendation Systems »
David Blei -
2016 : Panel Discussion »
Shakir Mohamed · David Blei · Ryan Adams · José Miguel Hernández-Lobato · Ian Goodfellow · Yarin Gal -
2016 : Deep exponential families »
David Blei -
2016 : The Data-Fusion Problem: Causal Inference and Reinforcement Learning »
Elias Bareinboim -
2016 Workshop: Machine Learning for Spatiotemporal Forecasting »
Florin Popescu · Sergio Escalera · Xavier Baró · Stephane Ayache · Isabelle Guyon -
2016 : Gaming challenges and encouraging collaborations »
Sergio Escalera · Isabelle Guyon -
2016 Workshop: Challenges in Machine Learning: Gaming and Education »
Isabelle Guyon · Evelyne Viegas · Balázs Kégl · Ben Hamner · Sergio Escalera -
2016 Workshop: Advances in Approximate Bayesian Inference »
Tamara Broderick · Stephan Mandt · James McInerney · Dustin Tran · David Blei · Kevin Murphy · Andrew Gelman · Michael I Jordan -
2016 Demonstration: Biometric applications of CNNs: get a job at "Impending Technologies"! »
Sergio Escalera · Isabelle Guyon · Baiyu Chen · Marc Quintana · Umut Güçlü · Yağmur Güçlütürk · Xavier Baró · Rob van Lier · Carlos Andujar · Marcel A. J. van Gerven · Bernhard E Boser · Luke Wang -
2016 Poster: Scalable Adaptive Stochastic Optimization Using Random Projections »
Gabriel Krummenacher · Brian McWilliams · Yannic Kilcher · Joachim M Buhmann · Nicolai Meinshausen -
2016 Poster: Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels »
Ilya Tolstikhin · Bharath Sriperumbudur · Bernhard Schölkopf -
2016 Poster: Operator Variational Inference »
Rajesh Ranganath · Dustin Tran · Jaan Altosaar · David Blei -
2016 Poster: Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities »
Ruitong Huang · Tor Lattimore · András György · Csaba Szepesvari -
2016 Poster: The Generalized Reparameterization Gradient »
Francisco Ruiz · Michalis Titsias · David Blei -
2016 Poster: SDP Relaxation with Randomized Rounding for Energy Disaggregation »
Kiarash Shaloudegi · András György · Csaba Szepesvari · Wilsun Xu -
2016 Oral: SDP Relaxation with Randomized Rounding for Energy Disaggregation »
Kiarash Shaloudegi · András György · Csaba Szepesvari · Wilsun Xu -
2016 Poster: Exponential Family Embeddings »
Maja Rudolph · Francisco Ruiz · Stephan Mandt · David Blei -
2016 Poster: Consistent Kernel Mean Estimation for Functions of Random Variables »
Carl-Johann Simon-Gabriel · Adam Scibior · Ilya Tolstikhin · Bernhard Schölkopf -
2016 Tutorial: Variational Inference: Foundations and Modern Methods »
David Blei · Shakir Mohamed · Rajesh Ranganath -
2015 Workshop: Challenges in Machine Learning (CiML 2015): "Open Innovation" and "Coopetitions" »
Isabelle Guyon · Evelyne Viegas · Ben Hamner · Balázs Kégl -
2015 : Confidence intervals for the mixing time of a reversible Markov chain from a single sample path »
Csaba Szepesvari -
2015 Workshop: Advances in Approximate Bayesian Inference »
Dustin Tran · Tamara Broderick · Stephan Mandt · James McInerney · Shakir Mohamed · Alp Kucukelbir · Matthew D. Hoffman · Neil Lawrence · David Blei -
2015 Poster: Online Learning with Gaussian Payoffs and Side Observations »
Yifan Wu · András György · Csaba Szepesvari -
2015 Poster: Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path »
Daniel Hsu · Aryeh Kontorovich · Csaba Szepesvari -
2015 Poster: Linear Multi-Resource Allocation with Semi-Bandit Feedback »
Tor Lattimore · Yacov Crammer · Csaba Szepesvari -
2015 Poster: The Population Posterior and Bayesian Modeling on Streams »
James McInerney · Rajesh Ranganath · David Blei -
2015 Poster: Automatic Variational Inference in Stan »
Alp Kucukelbir · Rajesh Ranganath · Andrew Gelman · David Blei -
2015 Spotlight: Automatic Variational Inference in Stan »
Alp Kucukelbir · Rajesh Ranganath · Andrew Gelman · David Blei -
2015 Poster: Bandits with Unobserved Confounders: A Causal Approach »
Elias Bareinboim · Andrew Forney · Judea Pearl -
2015 Poster: Combinatorial Cascading Bandits »
Branislav Kveton · Zheng Wen · Azin Ashkan · Csaba Szepesvari -
2015 Poster: BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions »
Dominik Rothenhäusler · Christina Heinze-Deml · Jonas Peters · Nicolai Meinshausen -
2015 Poster: Copula variational inference »
Dustin Tran · David Blei · Edo M Airoldi -
2014 Workshop: Novel Trends and Applications in Reinforcement Learning »
Csaba Szepesvari · Marc Deisenroth · Sergey Levine · Pedro Ortega · Brian Ziebart · Emma Brunskill · Naftali Tishby · Gerhard Neumann · Daniel Lee · Sridhar Mahadevan · Pieter Abbeel · David Silver · Vicenç Gómez -
2014 Workshop: High-energy particle physics, machine learning, and the HiggsML data challenge (HEPML) »
Glen Cowan · Balázs Kégl · Kyle Cranmer · Gábor Melis · Tim Salimans · Vladimir Vava Gligorov · Daniel Whiteson · Lester Mackey · Wojciech Kotlowski · Roberto Díaz Morales · Pierre Baldi · Cecile Germain · David Rousseau · Isabelle Guyon · Tianqi Chen -
2014 Workshop: Challenges in Machine Learning workshop (CiML 2014) »
Isabelle Guyon · Evelyne Viegas · Percy Liang · Olga Russakovsky · Rinat Sergeev · Gábor Melis · Michele Sebag · Gustavo Stolovitzky · Jaume Bacardit · Michael S Kim · Ben Hamner -
2014 Poster: Transportability from Multiple Environments with Limited Experiments: Completeness Results »
Elias Bareinboim · Judea Pearl -
2014 Poster: Universal Option Models »
hengshuai yao · Csaba Szepesvari · Richard Sutton · Joseph Modayil · Shalabh Bhatnagar -
2014 Spotlight: Transportability from Multiple Environments with Limited Experiments: Completeness Results »
Elias Bareinboim · Judea Pearl -
2014 Poster: Kernel Mean Estimation via Spectral Filtering »
Krikamol Muandet · Bharath Sriperumbudur · Bernhard Schölkopf -
2013 Workshop: Modern Nonparametric Methods in Machine Learning »
Arthur Gretton · Mladen Kolar · Samory Kpotufe · John Lafferty · Han Liu · Bernhard Schölkopf · Alexander Smola · Rob Nowak · Mikhail Belkin · Lorenzo Rosasco · peter bickel · Yue Zhao -
2013 Workshop: NIPS 2013 Workshop on Causality: Large-scale Experiment Design and Inference of Causal Mechanisms »
Isabelle Guyon · Leon Bottou · Bernhard Schölkopf · Alexander Statnikov · Evelyne Viegas · james m robins -
2013 Poster: Online Learning with Costly Features and Labels »
Navid Zolghadr · Gábor Bartók · Russell Greiner · András György · Csaba Szepesvari -
2013 Poster: The Randomized Dependence Coefficient »
David Lopez-Paz · Philipp Hennig · Bernhard Schölkopf -
2013 Poster: Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. »
Michel Besserve · Nikos K Logothetis · Bernhard Schölkopf -
2013 Poster: Transportability from Multiple Environments with Limited Experiments »
Elias Bareinboim · Sanghack Lee · Vasant Honavar · Judea Pearl -
2013 Poster: Causal Inference on Time Series using Restricted Structural Equation Models »
Jonas Peters · Dominik Janzing · Bernhard Schölkopf -
2013 Poster: Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions »
Yasin Abbasi Yadkori · Peter Bartlett · Varun Kanade · Yevgeny Seldin · Csaba Szepesvari -
2013 Tutorial: Causes and Counterfactuals: Concepts, Principles and Tools. »
Judea Pearl · Elias Bareinboim -
2012 Poster: Learning from Distributions via Support Measure Machines »
Krikamol Muandet · Kenji Fukumizu · Francesco Dinuzzo · Bernhard Schölkopf -
2012 Session: Oral Session 6 »
Csaba Szepesvari -
2012 Spotlight: Learning from Distributions via Support Measure Machines »
Krikamol Muandet · Kenji Fukumizu · Francesco Dinuzzo · Bernhard Schölkopf -
2012 Poster: Deep Representations and Codes for Image Auto-Annotation »
Jamie Kiros · Csaba Szepesvari -
2012 Poster: Semi-Supervised Domain Adaptation with Non-Parametric Copulas »
David Lopez-Paz · José Miguel Hernández-Lobato · Bernhard Schölkopf -
2012 Demonstration: Gesture recognition with Kinect »
Isabelle Guyon -
2012 Spotlight: Semi-Supervised Domain Adaptation with Non-Parametric Copulas »
David Lopez-Paz · José Miguel Hernández-Lobato · Bernhard Schölkopf -
2012 Poster: The representer theorem for Hilbert spaces: a necessary and sufficient condition »
Francesco Dinuzzo · Bernhard Schölkopf -
2011 Workshop: Philosophy and Machine Learning »
Marcello Pelillo · Joachim M Buhmann · Tiberio Caetano · Bernhard Schölkopf · Larry Wasserman -
2011 Workshop: Cosmology meets Machine Learning »
Michael Hirsch · Sarah Bridle · Bernhard Schölkopf · Phil Marshall · Stefan Harmeling · Mark Girolami -
2011 Poster: Improved Algorithms for Linear Stochastic Bandits »
Yasin Abbasi Yadkori · David Pal · Csaba Szepesvari -
2011 Spotlight: Improved Algorithms for Linear Stochastic Bandits »
Yasin Abbasi Yadkori · David Pal · Csaba Szepesvari -
2011 Invited Talk: From kernels to causal inference »
Bernhard Schölkopf -
2011 Poster: Crowdclustering »
Ryan G Gomes · Peter Welinder · Andreas Krause · Pietro Perona -
2011 Poster: Predicting response time and error rates in visual search »
Bo Chen · Vidhya Navalpakkam · Pietro Perona -
2011 Poster: Recovering Intrinsic Images with a Global Sparsity Prior on Reflectance »
Peter Gehler · Carsten Rother · Martin Kiefel · Lumin Zhang · Bernhard Schölkopf -
2011 Poster: Causal Discovery with Cyclic Additive Noise Models »
Joris M Mooij · Dominik Janzing · Tom Heskes · Bernhard Schölkopf -
2010 Spotlight: Online Markov Decision Processes under Bandit Feedback »
Gergely Neu · András György · András Antos · Csaba Szepesvari -
2010 Spotlight: Switched Latent Force Models for Movement Segmentation »
Mauricio A Alvarez · Jan Peters · Bernhard Schölkopf · Neil D Lawrence -
2010 Oral: The Multidimensional Wisdom of Crowds »
Peter Welinder · Steve Branson · Serge Belongie · Pietro Perona -
2010 Poster: The Multidimensional Wisdom of Crowds »
Peter Welinder · Steve Branson · Serge Belongie · Pietro Perona -
2010 Poster: Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake »
Stefan Harmeling · Michael Hirsch · Bernhard Schölkopf -
2010 Poster: Switched Latent Force Models for Movement Segmentation »
Mauricio A Alvarez · Jan Peters · Bernhard Schölkopf · Neil D Lawrence -
2010 Poster: Probabilistic latent variable models for distinguishing between cause and effect »
Joris M Mooij · Oliver Stegle · Dominik Janzing · Kun Zhang · Bernhard Schölkopf -
2010 Poster: Online Markov Decision Processes under Bandit Feedback »
Gergely Neu · András György · Csaba Szepesvari · András Antos -
2010 Poster: Discriminative Clustering by Regularized Information Maximization »
Ryan G Gomes · Andreas Krause · Pietro Perona -
2010 Poster: Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs »
David Pal · Barnabas Poczos · Csaba Szepesvari -
2010 Poster: Parametric Bandits: The Generalized Linear Case »
Sarah Filippi · Olivier Cappé · Aurélien Garivier · Csaba Szepesvari -
2010 Poster: Error Propagation for Approximate Policy and Value Iteration »
Amir-massoud Farahmand · Remi Munos · Csaba Szepesvari -
2009 Workshop: Connectivity Inference in Neuroimaging »
Karl Friston · Moritz Grosse-Wentrup · Uta Noppeney · Bernhard Schölkopf -
2009 Workshop: Clustering: Science or art? Towards principled approaches »
Margareta Ackerman · Shai Ben-David · Avrim Blum · Isabelle Guyon · Ulrike von Luxburg · Robert Williamson · Reza Zadeh -
2009 Mini Symposium: Causality and Time Series Analysis »
Florin Popescu · Isabelle Guyon · Guido Nolte -
2009 Poster: Multi-Step Dyna Planning for Policy Evaluation and Control »
Hengshuai Yao · Richard Sutton · Shalabh Bhatnagar · Dongcui Diao · Csaba Szepesvari -
2009 Poster: Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions »
Bharath Sriperumbudur · Kenji Fukumizu · Arthur Gretton · Gert Lanckriet · Bernhard Schölkopf -
2009 Oral: Kernel Choice and Classifiability for RKHS Embeddings of Probability Distributions »
Bharath Sriperumbudur · Kenji Fukumizu · Arthur Gretton · Gert Lanckriet · Bernhard Schölkopf -
2009 Poster: A General Projection Property for Distribution Families »
Yao-Liang Yu · Yuxi Li · Dale Schuurmans · Csaba Szepesvari -
2009 Demonstration: Causality Workbench »
Isabelle Guyon -
2009 Poster: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation »
Hamid R Maei · Csaba Szepesvari · Shalabh Batnaghar · Doina Precup · David Silver · Richard Sutton -
2009 Spotlight: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation »
Hamid R Maei · Csaba Szepesvari · Shalabh Batnaghar · Doina Precup · David Silver · Richard Sutton -
2008 Workshop: Causality: objectives and assessment »
Isabelle Guyon · Dominik Janzing · Bernhard Schölkopf -
2008 Mini Symposium: Computational Photography »
Bill Freeman · Bernhard Schölkopf -
2008 Poster: Characteristic Kernels on Groups and Semigroups »
Kenji Fukumizu · Bharath Sriperumbudur · Arthur Gretton · Bernhard Schölkopf -
2008 Poster: Online Optimization in X-Armed Bandits »
Sebastien Bubeck · Remi Munos · Gilles Stoltz · Csaba Szepesvari -
2008 Oral: Characteristic Kernels on Groups and Semigroups »
Kenji Fukumizu · Bharath Sriperumbudur · Arthur Gretton · Bernhard Schölkopf -
2008 Poster: Nonlinear causal discovery with additive noise models »
Patrik O Hoyer · Dominik Janzing · Joris M Mooij · Jonas Peters · Bernhard Schölkopf -
2008 Poster: Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance »
Jeremy Hill · Jason Farquhar · Suzanne Martens · Felix Bießmann · Bernhard Schölkopf -
2008 Poster: Bayesian Experimental Design of Magnetic Resonance Imaging Sequences »
Matthias Seeger · Hannes Nickisch · Rolf Pohmann · Bernhard Schölkopf -
2008 Poster: Regularized Policy Iteration »
Amir-massoud Farahmand · Mohammad Ghavamzadeh · Csaba Szepesvari · Shie Mannor -
2008 Spotlight: Nonlinear causal discovery with additive noise models »
Patrik O Hoyer · Dominik Janzing · Joris M Mooij · Jonas Peters · Bernhard Schölkopf -
2008 Spotlight: Bayesian Experimental Design of Magnetic Resonance Imaging Sequences »
Matthias Seeger · Hannes Nickisch · Rolf Pohmann · Bernhard Schölkopf -
2008 Spotlight: Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance »
Jeremy Hill · Jason Farquhar · Suzanne Martens · Felix Bießmann · Bernhard Schölkopf -
2008 Poster: A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approxi »
Richard Sutton · Csaba Szepesvari · Hamid R Maei -
2008 Poster: An empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis »
Gabriele B Schweikert · Christian Widmer · Bernhard Schölkopf · Gunnar Rätsch -
2008 Poster: Diffeomorphic Dimensionality Reduction »
Christian Walder · Bernhard Schölkopf -
2007 Spotlight: Kernel Measures of Conditional Dependence »
Kenji Fukumizu · Arthur Gretton · Xiaohai Sun · Bernhard Schölkopf -
2007 Poster: An Analysis of Inference with the Universum »
Fabian H Sinz · Olivier Chapelle · Alekh Agarwal · Bernhard Schölkopf -
2007 Poster: Kernel Measures of Conditional Dependence »
Kenji Fukumizu · Arthur Gretton · Xiaohai Sun · Bernhard Schölkopf -
2007 Spotlight: An Analysis of Inference with the Universum »
Fabian H Sinz · Olivier Chapelle · Alekh Agarwal · Bernhard Schölkopf -
2007 Demonstration: CLOP: a Matlab Learning Object Package »
Amir Reza Saffari Azar Alamdari · Isabelle Guyon · Hugo Jair Escalante · Gökhan H Bakir · Gavin Cawley -
2007 Spotlight: A Kernel Statistical Test of Independence »
Arthur Gretton · Kenji Fukumizu · Choon Hui Teo · Le Song · Bernhard Schölkopf · Alexander Smola -
2007 Poster: A Kernel Statistical Test of Independence »
Arthur Gretton · Kenji Fukumizu · Choon Hui Teo · Le Song · Bernhard Schölkopf · Alexander Smola -
2007 Poster: Fitted Q-iteration in continuous action-space MDPs »
Remi Munos · András Antos · Csaba Szepesvari -
2006 Workshop: Multi-level Inference Workshop and Model Selection Game »
Isabelle Guyon -
2006 Poster: Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions »
Christian Walder · Bernhard Schölkopf · Olivier Chapelle -
2006 Poster: Learning Dense 3D Correspondence »
Florian Steinke · Bernhard Schölkopf · Volker Blanz -
2006 Poster: A Local Learning Approach for Clustering »
Mingrui Wu · Bernhard Schölkopf -
2006 Poster: Graph-Based Visual Saliency »
Jonathan Harel · Christof Koch · Pietro Perona -
2006 Talk: Graph-Based Visual Saliency »
Jonathan Harel · Christof Koch · Pietro Perona -
2006 Poster: A Kernel Method for the Two-Sample-Problem »
Arthur Gretton · Karsten Borgwardt · Malte J Rasch · Bernhard Schölkopf · Alexander Smola -
2006 Poster: Correcting Sample Selection Bias by Unlabeled Data »
Jiayuan Huang · Alexander Smola · Arthur Gretton · Karsten Borgwardt · Bernhard Schölkopf -
2006 Spotlight: Correcting Sample Selection Bias by Unlabeled Data »
Jiayuan Huang · Alexander Smola · Arthur Gretton · Karsten Borgwardt · Bernhard Schölkopf -
2006 Talk: A Kernel Method for the Two-Sample-Problem »
Arthur Gretton · Karsten Borgwardt · Malte J Rasch · Bernhard Schölkopf · Alexander Smola -
2006 Poster: A Nonparametric Approach to Bottom-Up Visual Saliency »
Wolf Kienzle · Felix A Wichmann · Bernhard Schölkopf · Matthias Franz -
2006 Poster: Learning with Hypergraphs: Clustering, Classification, and Embedding »
Denny Zhou · Jiayuan Huang · Bernhard Schölkopf