Jonathan Baxter

Publication Activity (10 Years)

Years Active: 1995-2020
Publications (10 Years): 10

Top Topics

Theoretical Models

Matrix Multiplication

Distortion Measure

Top Venues

Publications

Jonathan Baxter
Theoretical Models of Learning to Learn. CoRR (2020)
Douglas Aberdeen, Jonathan Baxter
General Matrix-Matrix Multiplication Using SIMD features of the PIII. CoRR (2019)
Jonathan Baxter
A Bayesian/Information Theoretic Model of Bias Learning. CoRR (2019)
Jonathan Baxter
Some observations concerning Off Training Set (OTS) error. CoRR (2019)
Jonathan Baxter
Learning Model Bias. CoRR (2019)
Jonathan Baxter
The Canonical Distortion Measure for Vector Quantization and Function Approximation. CoRR (2019)
Jonathan Baxter
Learning Internal Representations (PhD Thesis). CoRR (2019)
Peter L. Bartlett, Jonathan Baxter
Hebbian Synaptic Modifications in Spiking Neurons that Learn. CoRR (2019)
Douglas Aberdeen, Jonathan Baxter, Robert Edwards
92c/MFlops/s, Ultra-Large-Scale Neural-Network Training on a PIII Cluster. CoRR (2019)
Jonathan Baxter
Learning internal representations. CoRR (2019)
Peter L. Bartlett, Jonathan Baxter, Lex Weaver
Experiments with Infinite-Horizon, Policy-Gradient Estimation CoRR (2011)
Jonathan Baxter
A Model of Inductive Bias Learning CoRR (2011)
Peter L. Bartlett, Jonathan Baxter
Infinite-Horizon Policy-Gradient Estimation CoRR (2011)
Dan Cosley, Jonathan Baxter, Soyoung Lee, Brian Alson, Saeko Nomura, Phil Adams, Chethan Sarabu, Geri Gay
A tag in the hand: supporting semantic, social, and spatial navigation in museums. CHI (2009)
Dan Cosley, Kathy Akey, Brian Alson, Jonathan Baxter, Mark Broomfield, Soyoung Lee, Chethan Sarabu
Using technologies to support reminiscence. BCS HCI (2009)
Dan Cosley, Joel Lewenstein, Andrew Herman, Jenna Holloway, Jonathan Baxter, Saeko Nomura, Kirsten Boehner, Geri Gay
ArtLinks: fostering social awareness and reflection in museums. CHI (2008)
Evan Greensmith, Peter L. Bartlett, Jonathan Baxter
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning. J. Mach. Learn. Res. 5 (2004)
Peter L. Bartlett, Jonathan Baxter
Estimation and Approximation Bounds for Gradient-Based Reinforcement Learning. J. Comput. Syst. Sci. 64 (1) (2002)
Douglas Aberdeen, Jonathan Baxter
Scalable Internal-State Policy-Gradient Methods for POMDPs. ICML (2002)
Jonathan Baxter, Peter L. Bartlett
Infinite-Horizon Policy-Gradient Estimation. J. Artif. Intell. Res. 15 (2001)
Nigel Tao, Jonathan Baxter, Lex Weaver
A Multi-Agent Policy-Gradient Approach to Network Routing. ICML (2001)
Evan Greensmith, Peter L. Bartlett, Jonathan Baxter
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning. NIPS (2001)
Jonathan Baxter, Peter L. Bartlett, Lex Weaver
Experiments with Infinite-Horizon, Policy-Gradient Estimation. J. Artif. Intell. Res. 15 (2001)
Douglas Aberdeen, Jonathan Baxter
Emmerald: a fast matrix-matrix multiply using Intel's SSE instructions. Concurr. Comput. Pract. Exp. 13 (2) (2001)
Douglas Aberdeen, Jonathan Baxter
General Matrix-Matrix Multiplication Using SIMD Features of the PIII (Research Note). Euro-Par (2000)
Llew Mason, Peter L. Bartlett, Jonathan Baxter
Improved Generalization Through Explicit Optimization of Margins. Mach. Learn. 38 (3) (2000)
Jonathan Baxter, Peter L. Bartlett
Reinforcement Learning in POMDP's via Direct Gradient Ascent. ICML (2000)
Jonathan Baxter
A Model of Inductive Bias Learning. J. Artif. Intell. Res. 12 (2000)
Peter L. Bartlett, Jonathan Baxter
Estimation and Approximation Bounds for Gradient-Based Reinforcement Learning. COLT (2000)
Jonathan Baxter, Peter L. Bartlett
Direct gradient-based reinforcement learning. ISCAS (2000)
Peter L. Bartlett, Jonathan Baxter
Stochastic optimization of controlled partially observable Markov decision processes. CDC (2000)
Jonathan Baxter, Andrew Tridgell, Lex Weaver
Learning to Play Chess Using Temporal Differences. Mach. Learn. 40 (3) (2000)
Douglas Aberdeen, Jonathan Baxter, Robert Edwards
98¢/Mflops/s, Ultra-Large-Scale Neural-Network Training on a PIII Cluster. SC (2000)
Jonathan Baxter, Nicolò Cesa-Bianchi
Guest Editors' Introduction. Mach. Learn. 37 (3) (1999)
Jonathan Baxter, Andrew Tridgell, Lex Weaver
KnightCap: A chess program that learns by combining TD(lambda) with game-tree search CoRR (1999)
Jonathan Baxter, Andrew Tridgell, Lex Weaver
TDLeaf(lambda): Combining Temporal Difference Learning with Game-Tree Search CoRR (1999)
Llew Mason, Jonathan Baxter, Peter L. Bartlett, Marcus R. Frean
Boosting Algorithms as Gradient Descent. NIPS (1999)
Jonathan Baxter, Andrew Tridgell, Lex Weaver
KnightCap: A Chess Programm That Learns by Combining TD(lambda) with Game-Tree Search. ICML (1998)
Jonathan Baxter, Andrew Tridgell, Lex Weaver
Experiments in Parameter Learning Using Temporal Differences. J. Int. Comput. Games Assoc. 21 (2) (1998)
Llew Mason, Peter L. Bartlett, Jonathan Baxter
Direct Optimization of Margins Improves Generalization in Combined Classifiers. NIPS (1998)
Jonathan Baxter, Peter L. Bartlett
The Canonical Distortion Measure in Feature Space and 1-NN Classification. NIPS (1997)
Jonathan Baxter
A Bayesian/Information Theoretic Model of Learning to Learn via Multiple Task Sampling. Mach. Learn. 28 (1) (1997)
Jonathan Baxter
The Canonical Distortion Measure for Vector Quantization and Function Approximation. ICML (1997)
Jonathan Baxter, Peter L. Bartlett
-Widths to Covering Numbers with some Applications to Neural Networks. EuroCOLT (1997)
Jonathan Baxter, John Shawe-Taylor
Learning to Compress Ergodic Sources. Data Compression Conference (1996)
Jonathan Baxter
A Bayesian/Information Theoretic Model of Bias Learning. COLT (1996)
Jonathan Baxter
Learning Model Bias. NIPS (1995)
Jonathan Baxter
Learning Internal Representations. COLT (1995)