2008 |
32 | EE | Julia Vogel,
Nando de Freitas:
Target-directed attention: Sequential decision-making for gaze planning.
ICRA 2008: 2372-2379 |
31 | EE | Peter Carbonetto,
Mark Schmidt,
Nando de Freitas:
An interior-point stochastic approximation method and an L1-regularized delta rule.
NIPS 2008: 233-240 |
30 | EE | 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) |
2007 |
29 | EE | 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 |
28 | EE | Eric Brochu,
Nando de Freitas,
Abhijeet Ghosh:
Active Preference Learning with Discrete Choice Data.
NIPS 2007 |
27 | EE | Matthew Hoffman,
Arnaud Doucet,
Nando de Freitas,
Ajay Jasra:
Bayesian Policy Learning with Trans-Dimensional MCMC.
NIPS 2007 |
26 | EE | 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 |
2006 |
25 | EE | Yizheng Cai,
Nando de Freitas,
James J. Little:
Robust Visual Tracking for Multiple Targets.
ECCV (4) 2006: 107-118 |
24 | EE | 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 |
23 | EE | Peter Carbonetto,
Nando de Freitas:
Conditional mean field.
NIPS 2006: 201-208 |
22 | EE | 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 |
2005 |
21 | | Maryam Mahdaviani,
Nando de Freitas,
Bob Fraser,
Firas Hamze:
Fast Computational Methods for Visually Guided Robots.
ICRA 2005: 138-143 |
20 | EE | Nando de Freitas,
Yang Wang,
Maryam Mahdaviani,
Dustin Lang:
Fast Krylov Methods for N-Body Learning.
NIPS 2005 |
19 | EE | Firas Hamze,
Nando de Freitas:
Hot Coupling: A Particle Approach to Inference and Normalization on Pairwise Undirected Graphs.
NIPS 2005 |
18 | EE | Mike Klaas,
Nando de Freitas,
Arnaud Doucet:
Toward Practical N2 Monte Carlo: the Marginal Particle Filter.
UAI 2005: 308-315 |
17 | EE | Nando de Freitas,
Hendrik Kück:
Learning about Individuals from Group Statistics.
UAI 2005: 332-339 |
16 | EE | Peter Carbonetto,
Jacek Kisynski,
Nando de Freitas,
David Poole:
Nonparametric Bayesian Logic.
UAI 2005: 85-93 |
2004 |
15 | EE | 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 |
14 | EE | Peter Carbonetto,
Nando de Freitas,
Kobus Barnard:
A Statistical Model for General Contextual Object Recognition.
ECCV (1) 2004: 350-362 |
13 | EE | Hendrik Kück,
Peter Carbonetto,
Nando de Freitas:
A Constrained Semi-supervised Learning Approach to Data Association.
ECCV (3) 2004: 1-12 |
12 | EE | Dustin Lang,
Nando de Freitas:
Beat Tracking the Graphical Model Way.
NIPS 2004 |
11 | EE | Firas Hamze,
Nando de Freitas:
From Fields to Trees.
UAI 2004: 243-250 |
2003 |
10 | EE | 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) |
9 | | 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) |
2002 |
8 | EE | Rubén Morales-Menéndez,
Nando de Freitas,
David Poole:
Real-Time Monitoring of Complex Industrial Processes with Particle Filters.
NIPS 2002: 1433-1440 |
7 | EE | Eric Brochu,
Nando de Freitas:
"Name That Song!" A Probabilistic Approach to Querying on Music and Text.
NIPS 2002: 1505-1512 |
2001 |
6 | EE | Christophe Andrieu,
Nando de Freitas,
Arnaud Doucet:
Rao-Blackwellised Particle Filtering via Data Augmentation.
NIPS 2001: 561-567 |
5 | EE | Nando de Freitas,
Pedro A. d. F. R. Højen-Sørensen,
Stuart J. Russell:
Variational MCMC.
UAI 2001: 120-127 |
4 | EE | Christophe Andrieu,
Nando de Freitas,
Arnaud Doucet:
Robust Full Bayesian Learning for Radial Basis Networks.
Neural Computation 13(10): 2359-2407 (2001) |
2000 |
3 | | Rudolph van der Merwe,
Arnaud Doucet,
Nando de Freitas,
Eric A. Wan:
The Unscented Particle Filter.
NIPS 2000: 584-590 |
2 | EE | Christophe Andrieu,
Nando de Freitas,
Arnaud Doucet:
Reversible Jump MCMC Simulated Annealing for Neural Networks.
UAI 2000: 11-18 |
1 | EE | Arnaud Doucet,
Nando de Freitas,
Kevin P. Murphy,
Stuart J. Russell:
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.
UAI 2000: 176-183 |