|
Editors' Introduction | | 1 - 12
|
|
Sanjay Jain,
Rémi Munos,
Frank Stephan,
and
Thomas Zeugmann.
|
|
| |
|
| |
|
FULL
INVITED PAPERS
| |
|
| |
|
Learning and Optimizing with Preferences,
Abstract.
| | 13 - 21
|
|
Nir Ailon
| |
|
Efficient Algorithms for Combinatorial Online Prediction,
Abstract.
| | 22 - 32
|
|
Eiji Takimoto
and
Kohei Hatano
| |
|
Exact Learning from Membership Queries: Some Techniques, Results
and New Directions,
Abstract.
| | 33 - 52
|
|
Nader H. Bshouty
| |
|
|
|
| |
|
REGULAR
CONTRIBUTIONS
| |
|
| |
|
|
|
|
| |
|
| |
|
Online Learning
| |
|
| |
|
Universal Algorithm for Trading in Stock Market Based on the
Method of Calibration,
Abstract.
| | 53 - 67
|
|
Vladimir V. V'yugin,
| |
|
Combinatorial Online Prediction via Metarounding,
Abstract.
| | 68 - 82
|
|
Takahiro Fujita,
Kohei Hatano, and
Eiji Takimoto
| |
|
On Competitive Recommendations,
Abstract.
| | 83 - 97
|
|
Jara Uitto and
Roger Wattenhofer
| |
|
Online PCA with Optimal Regrets,
Abstract.
| | 98 - 112
|
|
Jiazhong Nie,
Wojciech Kotłowski and
Manfred Warmuth
|
| |
|
Inductive Inference
| |
|
| |
|
Partial Learning of Recursively Enumerable Languages,
Abstract.
| | 113 - 127
|
|
Ziyuan Gao,
Frank Stephan, and
Sandra Zilles
| |
|
Topological Separations in Inductive Inference,
Abstract.
| | 128 - 142
|
|
John Case and
Timo Kötzing
| |
|
PAC Learning of Some Subclasses of Context-Free Grammars with
Basic Distributional Properties from Positive Data,
Abstract.
| | 143 - 157
|
|
Chihiro Shibata and
Ryo Yoshinaka
| |
|
Universal Knowledge-Seeking Agents for Stochastic Environments,
Abstract.
| | 158 - 172
|
|
Laurent Orseau,
Tor Lattimore, and
Marcus Hutter
|
|
| |
|
| |
|
Teaching and Learning from Queries
| |
|
| |
|
Order Compression Schemes,
Abstract.
| | 173 - 187
|
|
Malte Darnstädt,
Thorsten Doliwa,
Hans Ulrich Simon,
and
Sandra Zilles.
| |
|
Learning a Bounded-Degree Tree Using Separator Queries,
Abstract.
| | 188 - 202
|
|
M. Jagadish and Anindya Sen
|
|
| |
|
| |
|
Bandit Theory
| |
|
| |
|
Faster Hoeffding Racing: Bernstein Races via
Jackknife Estimates,
Abstract.
| | 203 - 217
|
|
Po-Ling Loh and
Sebastian Nowozin
| |
|
Robust Risk-Averse Stochastic Multi-armed Bandits,
Abstract.
| | 218 - 233
|
|
Odalric-Ambrym Maillard
| |
|
An Efficient Algorithm for Learning with Semi-bandit Feedback,
Abstract.
| | 234 - 248
|
|
Gergely Neu and
Gábor Bartók
|
|
| |
|
| |
|
Statistical Learning Theory
| |
|
| |
|
Differentially-Private Learning of Low Dimensional Manifolds,
Abstract.
| | 249 - 263
|
|
Anna Choromanska,
Krzysztof Choromanski,
Geetha Jagannathan, and
Claire Monteleoni
| |
|
Generalization and Robustness of Batched Weighted Average
Algorithm with V-Geometrically Ergodic Markov Data,
Abstract.
| | 264 - 278
|
|
Nguyen Viet Cuong, Lam Si Tung Ho, and Vu Dinh
| |
|
Adaptive Metric Dimensionality Reduction,
Abstract.
| | 279 - 293
|
|
Lee-Ad Gottlieb,
Aryeh Kontorovich, and
Robert Krauthgamer
| |
|
Dimension-Adaptive Bounds on Compressive FLD Classification,
Abstract.
| | 294 - 308
|
|
Ata Kaban and
Robert Durrant
|
|
| |
|
| |
|
Bayesian/Stochastic Learning
| |
|
| |
|
Bayesian Methods for Low-Rank Matrix Estimation: Short
Survey and Theoretical Study,
Abstract.
| | 309 - 323
|
|
Pierre Alquier
| |
|
Concentration and Confidence for Discrete Bayesian Sequence Predictors,
Abstract.
| | 324 - 338
|
|
Tor Lattimore,
Marcus Hutter and
Peter Sunehag
| |
|
Algorithmic Connections between Active Learning and Stochastic
Convex Optimization,
Abstract.
| | 339 - 353
|
|
Aaditya Ramdas and
Aarti Singh
|
|
| |
|
| |
|
Unsupervised/Semi-Supervised Learning
| |
|
| |
|
Unsupervised Model-Free Representation Learning,
Abstract.
| | 354 - 366
|
|
Daniil Ryabko
| |
|
Fast Spectral Clustering via the Nyström Method,
Abstract.
| | 367 - 381
|
|
Anna Choromanska,
Tony Jebara,
Hyungtae Kim, Mahesh Mohan, and
Claire Monteleoni
| |
|
Nonparametric Multiple Change Point Estimation in Highly
Dependent Time Series,
Abstract.
| | 382 - 396
|
|
Azadeh Khaleghi and
Daniil Ryabko
| |
|
|
Author Index
| | 397
|
back to the ALT 2013
Proceedings Page
