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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 23: Conference on Learning Theory, 25-27 June 2012, Edinburgh, Scotland

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Editors: Shie Mannor, Nathan Srebro, Robert C. Williamson

[bib][citeproc]

Contents:

  • Preface
  • Accepted Papers

Filter Authors: Filter Titles:

Preface

Preface

; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:1.1-1.2

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Accepted Papers

Unsupervised SVMs: On the Complexity of the Furthest Hyperplane Problem

Zohar Karnin, Edo Liberty, Shachar Lovett, Roy Schwartz, Omri Weinstein; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:2.1-2.17

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(weak) Calibration is Computationally Hard

Elad Hazan, Sham M. Kakade; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:3.1-3.10

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Learning Valuation Functions

Maria Florina Balcan, Florin Constantin, Satoru Iwata, Lei Wang; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:4.1-4.24

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Unified Algorithms for Online Learning and Competitive Analysis

Niv Buchbinder, Shahar Chen, Joshep (Seffi) Naor, Ohad Shamir; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:5.1-5.18

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Online Optimization with Gradual Variations

Chao-Kai Chiang, Tianbao Yang, Chia-Jung Lee, Mehrdad Mahdavi, Chi-Jen Lu, Rong Jin, Shenghuo Zhu; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:6.1-6.20

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The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators

Fares Hedayati, Peter L. Bartlett; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:7.1-7.13

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PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model

Taiji Suzuki; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:8.1-8.20

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Random Design Analysis of Ridge Regression

Daniel Hsu, Sham M. Kakade, Tong Zhang; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:9.1-9.24

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Reconstruction from Anisotropic Random Measurements

Mark Rudelson, Shuheng Zhou; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:10.1-10.24

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Toward a Noncommutative Arithmetic-geometric Mean Inequality: Conjectures, Case-studies, and Consequences

Benjamin Recht, Christopher Re; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:11.1-11.24

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L1 Covering Numbers for Uniformly Bounded Convex Functions

Adityanand Guntuboyina, Bodhisattva Sen; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:12.1-12.13

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Generalization Bounds for Online Learning Algorithms with Pairwise Loss Functions

Yuyang Wang, Roni Khardon, Dmitry Pechyony, Rosie Jones; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:13.1-13.22

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Attribute-Efficient Learning andWeight-Degree Tradeoffs for Polynomial Threshold Functions

Rocco Servedio, Li-Yang Tan, Justin Thaler; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:14.1-14.19

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Learning Functions of Halfspaces Using Prefix Covers

Parikshit Gopalan, Adam R. Klivans, Raghu Meka; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:15.1-15.10

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Computational Bounds on Statistical Query Learning

Vitaly Feldman, Varun Kanade; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:16.1-16.22

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Learning DNF Expressions from Fourier Spectrum

Vitaly Feldman; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:17.1-17.19

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Consistency of Nearest Neighbor Classification under Selective Sampling

Sanjoy Dasgupta; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:18.1-18.15

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Active Learning Using Smooth Relative Regret Approximations with Applications

Nir Ailon, Ron Begleiter, Esther Ezra; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:19.1-19.20

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Robust Interactive Learning

Maria Florina Balcan, Steve Hanneke; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:20.1-20.34

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Rare Probability Estimation under Regularly Varying Heavy Tails

Mesrob I. Ohannessian, Munther A. Dahleh; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:21.1-21.24

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Competitive Classification and Closeness Testing

Jayadev Acharya, Hirakendu Das, Ashkan Jafarpour, Alon Orlitsky, Shengjun Pan, Ananda Suresh; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:22.1-22.18

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Kernels Based Tests with Non-asymptotic Bootstrap Approaches for Two-sample Problems

Magalie Fromont, Béatrice Laurent, Matthieu Lerasle, Patricia Reynaud-Bouret; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:23.1-23.23

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Differentially Private Online Learning

Prateek Jain, Pravesh Kothari, Abhradeep Thakurta; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:24.1-24.34

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Private Convex Empirical Risk Minimization and High-dimensional Regression

Daniel Kifer, Adam Smith, Abhradeep Thakurta; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:25.1-25.40

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Distributed Learning, Communication Complexity and Privacy

Maria Florina Balcan, Avrim Blum, Shai Fine, Yishay Mansour; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:26.1-26.22

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A Characterization of Scoring Rules for Linear Properties

Jacob D. Abernethy, Rafael M. Frongillo; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:27.1-27.13

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Divergences and Risks for Multiclass Experiments

Dario García-García, Robert C. Williamson; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:28.1-28.20

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A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems

Takafumi Kanamori, Akiko Takeda, Taiji Suzuki; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:29.1-29.23

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New Bounds for Learning Intervals with Implications for Semi-Supervised Learning

David P. Helmbold, Philip M. Long; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:30.1-30.15

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Tight Bounds on Proper Equivalence Query Learning of DNF

Lisa Hellerstein, Devorah Kletenik, Linda Sellie, Rocco Servedio; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:31.1-31.18

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Distance Preserving Embeddings for General n-Dimensional Manifolds

Nakul Verma; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:32.1-32.28

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A Method of Moments for Mixture Models and Hidden Markov Models

Animashree Anandkumar, Daniel Hsu, Sham M. Kakade; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:33.1-33.34

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A Correlation Clustering Approach to Link Classification in Signed Networks

Nicoló Cesa-Bianchi, Claudio Gentile, Fabio Vitale, Giovanni Zappella; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:34.1-34.20

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Spectral Clustering of Graphs with General Degrees in the Extended Planted Partition Model

Kamalika Chaudhuri, Fan Chung, Alexander Tsiatas; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:35.1-35.23

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Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries

Mikhail Belkin, Qichao Que, Yusu Wang, Xueyuan Zhou; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:36.1-36.26

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Exact Recovery of Sparsely-Used Dictionaries

Daniel A. Spielman, Huan Wang, John Wright; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:37.1-37.18

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Near-Optimal Algorithms for Online Matrix Prediction

Elad Hazan, Satyen Kale, Shai Shalev-Shwartz; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:38.1-38.13

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Analysis of Thompson Sampling for the Multi-armed Bandit Problem

Shipra Agrawal, Navin Goyal; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:39.1-39.26

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Autonomous Exploration For Navigating In MDPs

Shiau Hong Lim, Peter Auer; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:40.1-40.24

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Towards Minimax Policies for Online Linear Optimization with Bandit Feedback

Sébastien Bubeck, Nicoló Cesa-Bianchi, Sham M. Kakade; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:41.1-41.14

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The Best of Both Worlds: Stochastic and Adversarial Bandits

Sébastien Bubeck, Aleksandrs Slivkins; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:42.1-42.23

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Open Problem: Regret Bounds for Thompson Sampling

Lihong Li, Olivier Chapelle; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:43.1-43.3

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Open Problem: Better Bounds for Online Logistic Regression

H. Brendan McMahan, Matthew Streeter; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:44.1-44.3

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Open Problem: Learning Dynamic Network Models from a Static Snapshot

Jan Ramon, Constantin Comendant; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:45.1-45.3

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Open Problem: Does AdaBoost Always Cycle?

Cynthia Rudin, Robert E. Schapire, Ingrid Daubechies; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:46.1-46.4

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Open Problem: Is Averaging Needed for Strongly Convex Stochastic Gradient Descent?

Ohad Shamir; Proceedings of the 25th Annual Conference on Learning Theory, PMLR 23:47.1-47.3

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此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。