Nando de Freitas

Firas Hamze, Ziyu Wang, Nando de Freitas: Self-Avoiding Random Dynamics on Integer Complex Systems. ACM Trans. Model. Comput. Simul. 23(1): 9 (2013)

Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, Nando de Freitas: Bayesian Optimization in a Billion Dimensions via Random Embeddings. CoRR abs/1301.1942 (2013)

Nando de Freitas, Pedro A. d. F. R. Højen-Sørensen, Michael I. Jordan, Stuart J. Russell: Variational MCMC. CoRR abs/1301.2266 (2013)

Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Reversible Jump MCMC Simulated Annealing for Neural Networks. CoRR abs/1301.3833 (2013)

Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart J. Russell: Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. CoRR abs/1301.3853 (2013)

Luke Bornn, Yutian Chen, Nando de Freitas, Mareija Eskelin, Jing Fang, Max Welling: Herded Gibbs Sampling. CoRR abs/1301.4168 (2013)

Nando de Freitas, Kevin P. Murphy: Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (2012). CoRR abs/1301.4604 (2013)

Matthew W. Hoffman, Bobak Shahriari, Nando de Freitas: Best arm identification via Bayesian gap-based exploration. CoRR abs/1303.6746 (2013)

David Buchman, Mark W. Schmidt, Shakir Mohamed, David Poole, Nando de Freitas: On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models. Journal of Machine Learning Research - Proceedings Track 22: 173-181 (2012)

Nimalan Mahendran, Ziyu Wang, Firas Hamze, Nando de Freitas: Adaptive MCMC with Bayesian Optimization. Journal of Machine Learning Research - Proceedings Track 22: 751-760 (2012)

Misha Denil, Loris Bazzani, Hugo Larochelle, Nando de Freitas: Learning Where to Attend with Deep Architectures for Image Tracking. Neural Computation 24(8): 2151-2184 (2012)

Michael A. Osborne, Roman Garnett, Kevin Swersky, Nando de Freitas: Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults. AAAI 2012

Byron Knoll, Nando de Freitas: A Machine Learning Perspective on Predictive Coding with PAQ8. DCC 2012: 377-386

Nando de Freitas, Alex J. Smola, Masrour Zoghi: Exponential Regret Bounds for Gaussian Process Bandits with Deterministic Observations. ICML 2012

Nando de Freitas, Kevin P. Murphy (Eds.): Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, Catalina Island, CA, USA, August 14-18, 2012. AUAI Press 2012

Benjamin M. Marlin, Nando de Freitas: Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood. CoRR abs/1202.3746 (2012)

Nando de Freitas, Alex J. Smola, Masrour Zoghi: Regret Bounds for Deterministic Gaussian Process Bandits. CoRR abs/1203.2177 (2012)

Mohamed Osama Ahmed, Pouyan T. Bibalan, Nando de Freitas, Simon Fauvel: Decentralized, Adaptive, Look-Ahead Particle Filtering. CoRR abs/1203.2394 (2012)

Firas Hamze, Nando de Freitas: Intracluster Moves for Constrained Discrete-Space MCMC. CoRR abs/1203.3484 (2012)

Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet: New inference strategies for solving Markov Decision Processes using reversible jump MCMC. CoRR abs/1205.2643 (2012)

Firas Hamze, Nando de Freitas: Large-Flip Importance Sampling. CoRR abs/1206.5239 (2012)

Peter Carbonetto, Jacek Kisynski, Nando de Freitas, David Poole: Nonparametric Bayesian Logic. CoRR abs/1207.1375 (2012)

Hendrik Kück, Nando de Freitas: Learning about individuals from group statistics. CoRR abs/1207.1393 (2012)

Mike Klaas, Nando de Freitas, Arnaud Doucet: Toward Practical N2 Monte Carlo: the Marginal Particle Filter. CoRR abs/1207.1396 (2012)

Firas Hamze, Nando de Freitas: From Fields to Trees. CoRR abs/1207.4149 (2012)

Misha Denil, Nando de Freitas: Recklessly Approximate Sparse Coding. CoRR abs/1208.0959 (2012)

Loris Bazzani, Nando de Freitas, Hugo Larochelle, Vittorio Murino, Jo-Anne Ting: Learning attentional policies for tracking and recognition in video with deep networks. ICML 2011: 937-944

Kevin Swersky, Marc'Aurelio Ranzato, David Buchman, Benjamin M. Marlin, Nando de Freitas: On Autoencoders and Score Matching for Energy Based Models. ICML 2011: 1201-1208

Matthew D. Hoffman, Eric Brochu, Nando de Freitas: Portfolio Allocation for Bayesian Optimization. UAI 2011: 327-336

Benjamin M. Marlin, Nando de Freitas: Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood. UAI 2011: 497-505

Byron Knoll, Nando de Freitas: A Machine Learning Perspective on Predictive Coding with PAQ. CoRR abs/1108.3298 (2011)

Misha Denil, Loris Bazzani, Hugo Larochelle, Nando de Freitas: Learning where to Attend with Deep Architectures for Image Tracking. CoRR abs/1109.3737 (2011)

Benjamin M. Marlin, Kevin Swersky, Bo Chen, Nando de Freitas: Inductive Principles for Restricted Boltzmann Machine Learning. Journal of Machine Learning Research - Proceedings Track 9: 509-516 (2010)

Kevin Swersky, Bo Chen, Benjamin M. Marlin, Nando de Freitas: A tutorial on stochastic approximation algorithms for training Restricted Boltzmann Machines and Deep Belief Nets. ITA 2010: 80-89

Eric Brochu, Tyson Brochu, Nando de Freitas: A Bayesian Interactive Optimization Approach to Procedural Animation Design. Symposium on Computer Animation 2010: 103-112

Firas Hamze, Nando de Freitas: Intracluster Moves for Constrained Discrete-Space MCMC. UAI 2010: 236-243

Eric Brochu, Matthew D. Hoffman, Nando de Freitas: Hedging Strategies for Bayesian Optimization. CoRR abs/1009.5419 (2010)

Eric Brochu, Vlad M. Cora, Nando de Freitas: A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning. CoRR abs/1012.2599 (2010)

Ruben Martinez-Cantin, Nando de Freitas, Eric Brochu, José A. Castellanos, Arnaud Doucet: A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot. Auton. Robots 27(2): 93-103 (2009)

Matthew D. Hoffman, Nando de Freitas, Arnaud Doucet, Jan Peters: An Expectation Maximization Algorithm for Continuous Markov Decision Processes with Arbitrary Reward. Journal of Machine Learning Research - Proceedings Track 5: 232-239 (2009)

Hendrik Kück, Matthew D. Hoffman, Arnaud Doucet, Nando de Freitas: Inference and Learning for Active Sensing, Experimental Design and Control. IbPRIA 2009: 1-10

Matthias Hoffman, Hendrik Kück, Nando de Freitas, Arnaud Doucet: New inference strategies for solving Markov Decision Processes using reversible jump MCMC. UAI 2009: 223-231

Peter Carbonetto, Gyuri Dorkó, Cordelia Schmid, Hendrik Kück, Nando de Freitas: Learning to Recognize Objects with Little Supervision. International Journal of Computer Vision 77(1-3): 219-237 (2008)

Julia Vogel, Nando de Freitas: Target-directed attention: Sequential decision-making for gaze planning. ICRA 2008: 2372-2379

Peter Carbonetto, Mark W. Schmidt, Nando de Freitas: An interior-point stochastic approximation method and an L1-regularized delta rule. NIPS 2008: 233-240

Ruben Martinez-Cantin, Nando de Freitas, José A. Castellanos: Analysis of Particle Methods for Simultaneous Robot Localization and Mapping and a New Algorithm: Marginal-SLAM. ICRA 2007: 2415-2420

Eric Brochu, Nando de Freitas, Abhijeet Ghosh: Active Preference Learning with Discrete Choice Data. NIPS 2007

Matthew D. Hoffman, Arnaud Doucet, Nando de Freitas, Ajay Jasra: Bayesian Policy Learning with Trans-Dimensional MCMC. NIPS 2007

Ruben Martinez-Cantin, Nando de Freitas, Arnaud Doucet, José A. Castellanos: Active Policy Learning for Robot Planning and Exploration under Uncertainty. Robotics: Science and Systems 2007

Firas Hamze, Nando de Freitas: Large-Flip Importance Sampling. UAI 2007: 167-174

Peter Carbonetto, Gyuri Dorkó, Cordelia Schmid, Hendrik Kück, Nando de Freitas: A Semi-supervised Learning Approach to Object Recognition with Spatial Integration of Local Features and Segmentation Cues. Toward Category-Level Object Recognition 2006: 277-300

Yizheng Cai, Nando de Freitas, James J. Little: Robust Visual Tracking for Multiple Targets. ECCV (4) 2006: 107-118

Mike Klaas, Mark Briers, Nando de Freitas, Arnaud Doucet, Simon Maskell, Dustin Lang: Fast particle smoothing: if I had a million particles. ICML 2006: 481-488

Peter Carbonetto, Nando de Freitas: Conditional mean field. NIPS 2006: 201-208

Maryam Mahdaviani, Nando de Freitas, Bob Fraser, Firas Hamze: Fast Computational Methods for Visually Guided Robots. ICRA 2005: 138-143

Nando de Freitas, Yang Wang, Maryam Mahdaviani, Dustin Lang: Fast Krylov Methods for N-Body Learning. NIPS 2005

Firas Hamze, Nando de Freitas: Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs. NIPS 2005

Peter Carbonetto, Jacek Kisynski, Nando de Freitas, David Poole: Nonparametric Bayesian Logic. UAI 2005: 85-93

Mike Klaas, Nando de Freitas, Arnaud Doucet: Toward Practical N2 Monte Carlo: the Marginal Particle Filter. UAI 2005: 308-315

Nando de Freitas, Hendrik Kück: Learning about Individuals from Group Statistics. UAI 2005: 332-339

Hendrik Kück, Peter Carbonetto, Nando de Freitas: A Constrained Semi-supervised Learning Approach to Data Association. ECCV (3) 2004: 1-12

Kenji Okuma, Ali Taleghani, Nando de Freitas, James J. Little, David G. Lowe: A Boosted Particle Filter: Multitarget Detection and Tracking. ECCV (1) 2004: 28-39

Peter Carbonetto, Nando de Freitas, Kobus Barnard: A Statistical Model for General Contextual Object Recognition. ECCV (1) 2004: 350-362

Dustin Lang, Nando de Freitas: Beat Tracking the Graphical Model Way. NIPS 2004

Firas Hamze, Nando de Freitas: From Fields to Trees. UAI 2004: 243-250

Kobus Barnard, Pinar Duygulu, David A. Forsyth, Nando de Freitas, David M. Blei, Michael I. Jordan: Matching Words and Pictures. Journal of Machine Learning Research 3: 1107-1135 (2003)

Christophe Andrieu, Nando de Freitas, Arnaud Doucet, Michael I. Jordan: An Introduction to MCMC for Machine Learning. Machine Learning 50(1-2): 5-43 (2003)

Rubén Morales-Menéndez, Nando de Freitas, David Poole: Real-Time Monitoring of Complex Industrial Processes with Particle Filters. NIPS 2002: 1433-1440

Eric Brochu, Nando de Freitas: "Name That Song!" A Probabilistic Approach to Querying on Music and Text. NIPS 2002: 1505-1512

Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Robust Full Bayesian Learning for Radial Basis Networks. Neural Computation 13(10): 2359-2407 (2001)

Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Rao-Blackwellised Particle Filtering via Data Augmentation. NIPS 2001: 561-567

Nando de Freitas, Pedro A. d. F. R. Højen-Sørensen, Stuart J. Russell: Variational MCMC. UAI 2001: 120-127

Rudolph van der Merwe, Arnaud Doucet, Nando de Freitas, Eric A. Wan: The Unscented Particle Filter. NIPS 2000: 584-590

Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Reversible Jump MCMC Simulated Annealing for Neural Networks. UAI 2000: 11-18

Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart J. Russell: Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. UAI 2000: 176-183