惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Cisco Talos Blog
Cisco Talos Blog
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
爱范儿
爱范儿
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Jina AI
Jina AI
雷峰网
雷峰网
The Register - Security
The Register - Security
The Cloudflare Blog
博客园 - 【当耐特】
M
MIT News - Artificial intelligence
I
InfoQ
博客园 - 三生石上(FineUI控件)
H
Help Net Security
博客园 - 司徒正美
Vercel News
Vercel News
WordPress大学
WordPress大学
S
SegmentFault 最新的问题
云风的 BLOG
云风的 BLOG
B
Blog
Google DeepMind News
Google DeepMind News
B
Blog RSS Feed
L
LangChain Blog
人人都是产品经理
人人都是产品经理
GbyAI
GbyAI
T
The Blog of Author Tim Ferriss
T
Tailwind CSS Blog
aimingoo的专栏
aimingoo的专栏
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Recorded Future
Recorded Future
小众软件
小众软件
Martin Fowler
Martin Fowler
罗磊的独立博客
Stack Overflow Blog
Stack Overflow Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
酷 壳 – CoolShell
酷 壳 – CoolShell
腾讯CDC
CTFtime.org: upcoming CTF events
CTFtime.org: upcoming CTF events
Apple Machine Learning Research
Apple Machine Learning Research
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
博客园 - Franky
Hugging Face - Blog
Hugging Face - Blog
Y
Y Combinator Blog
V
Visual Studio Blog
F
Fortinet All Blogs
Microsoft Azure Blog
Microsoft Azure Blog
大猫的无限游戏
大猫的无限游戏
Engineering at Meta
Engineering at Meta
N
Netflix TechBlog - Medium
V
V2EX
Blog — PlanetScale
Blog — PlanetScale

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

[edit]

Volume 132: Algorithmic Learning Theory, 16-19 March 2021, Virtual Conference, Worldwide

[edit]

Editors: Vitaly Feldman, Katrina Ligett, Sivan Sabato

[bib][citeproc]

Filter Authors: Filter Titles:

Algorithmic Learning Theory 2021: Preface

; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1-2

[abs][Download PDF]

Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization

Jacob Abernethy, Kevin A. Lai, Andre Wibisono; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:3-47

[abs][Download PDF]

Differentially Private Assouad, Fano, and Le Cam

Jayadev Acharya, Ziteng Sun, Huanyu Zhang; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:48-78

[abs][Download PDF]

Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints

Jayadev Acharya, Peter Kairouz, Yuhan Liu, Ziteng Sun; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:79-98

[abs][Download PDF]

Efficient Algorithms for Stochastic Repeated Second-price Auctions

Juliette Achddou, Olivier Cappé, Aurélien Garivier; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:99-150

[abs][Download PDF]

Intervention Efficient Algorithms for Approximate Learning of Causal Graphs

Raghavendra Addanki, Andrew McGregor, Cameron Musco; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:151-184

[abs][Download PDF]

On the Sample Complexity of Privately Learning Unbounded High-Dimensional Gaussians

Ishaq Aden-Ali, Hassan Ashtiani, Gautam Kamath; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:185-216

[abs][Download PDF]

Stochastic Dueling Bandits with Adversarial Corruption

Arpit Agarwal, Shivani Agarwal, Prathamesh Patil; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:217-248

[abs][Download PDF]

A Deep Conditioning Treatment of Neural Networks

Naman Agarwal, Pranjal Awasthi, Satyen Kale; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:249-305

[abs][Download PDF]

Stochastic Top-$K$ Subset Bandits with Linear Space and Non-Linear Feedback

Mridul Agarwal, Vaneet Aggarwal, Christopher J. Quinn, Abhishek K. Umrawal; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:306-339

[abs][Download PDF]

Sequential prediction under log-loss with side information

Alankrita Bhatt, Young-Han Kim; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:340-344

[abs][Download PDF]

No-substitution k-means Clustering with Adversarial Order

Robi Bhattacharjee, Michal Moshkovitz; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:345-366

[abs][Download PDF]

Testing Product Distributions: A Closer Look

Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, N. V. Vinodchandran; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:367-396

[abs][Download PDF]

Online Boosting with Bandit Feedback

Nataly Brukhim, Elad Hazan; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:397-420

[abs][Download PDF]

Bounding, Concentrating, and Truncating: Unifying Privacy Loss Composition for Data Analytics

Mark Cesar, Ryan Rogers; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:421-457

[abs][Download PDF]

Learning and Testing Irreducible Markov Chains via the $k$-Cover Time

Siu On Chan, Qinghua Ding, Sing Hei Li; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:458-480

[abs][Download PDF]

Learning a mixture of two subspaces over finite fields

Aidao Chen, Anindya De, Aravindan Vijayaraghavan; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:481-504

[abs][Download PDF]

Asymptotically Optimal Strategies For Combinatorial Semi-Bandits in Polynomial Time

Thibaut Cuvelier, Richard Combes, Eric Gourdin; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:505-528

[abs][Download PDF]

An Efficient Algorithm for Cooperative Semi-Bandits

Riccardo Della Vecchia, Tommaso Cesari; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:529-552

[abs][Download PDF]

Last Round Convergence and No-Dynamic Regret in Asymmetric Repeated Games

Le Cong Dinh, Tri-Dung Nguyen, Alain B. Zemhoho, Long Tran-Thanh; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:553-577

[abs][Download PDF]

Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited

Omar Darwiche Domingues, Pierre Ménard, Emilie Kaufmann, Michal Valko; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:578-598

[abs][Download PDF]

Adversarial Online Learning with Changing Action Sets: Efficient Algorithms with Approximate Regret Bounds

Ehsan Emamjomeh-Zadeh, Chen-Yu Wei, Haipeng Luo, David Kempe; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:599-618

[abs][Download PDF]

A Technical Note on Non-Stationary Parametric Bandits: Existing Mistakes and Preliminary Solutions

Louis Faury, Yoan Russac, Marc Abeille, Clément Calauzènes; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:619-626

[abs][Download PDF]

Subspace Embeddings under Nonlinear Transformations

Aarshvi Gajjar, Cameron Musco; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:656-672

[abs][Download PDF]

Efficient sampling from the Bingham distribution

Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:673-685

[abs][Download PDF]

Near-tight Closure Bounds for the Littlestone and Threshold Dimensions

Badih Ghazi, Noah Golowich, Ravi Kumar, Pasin Manurangsi; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:686-696

[abs][Download PDF]

Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound

Steve Hanneke, Aryeh Kontorovich; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:697-721

[abs][Download PDF]

Submodular combinatorial information measures with applications in machine learning

Rishabh Iyer, Ninad Khargoankar, Jeff Bilmes, Himanshu Asanani; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:722-754

[abs][Download PDF]

Precise Minimax Regret for Logistic Regression with Categorical Feature Values

Philippe Jacquet, Gil Shamir, Wojciech Szpankowski; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:755-771

[abs][Download PDF]

Characterizing the implicit bias via a primal-dual analysis

Ziwei Ji, Matus Telgarsky; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:772-804

[abs][Download PDF]

Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback

Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:805-849

[abs][Download PDF]

Efficient Learning with Arbitrary Covariate Shift

Adam Tauman Kalai, Varun Kanade; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:850-864

[abs][Download PDF]

Adaptive Reward-Free Exploration

Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:865-891

[abs][Download PDF]

Unexpected Effects of Online no-Substitution $k$-means Clustering

Michal Moshkovitz; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:892-930

[abs][Download PDF]

Descent-to-Delete: Gradient-Based Methods for Machine Unlearning

Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:931-962

[abs][Download PDF]

Uncertainty quantification using martingales for misspecified Gaussian processes

Willie Neiswanger, Aaditya Ramdas; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:963-982

[abs][Download PDF]

Learning with Comparison Feedback: Online Estimation of Sample Statistics

Michela Meister, Sloan Nietert; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:983-1001

[abs][Download PDF]

Online Learning of Facility Locations

Stephen Pasteris, Ting He, Fabio Vitale, Shiqiang Wang, Mark Herbster; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1002-1050

[abs][Download PDF]

Statistical guarantees for generative models without domination

Nicolas Schreuder, Victor-Emmanuel Brunel, Arnak Dalalyan; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1051-1071

[abs][Download PDF]

Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance

Jie Shen, Chicheng Zhang; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1072-1113

[abs][Download PDF]

Self-Tuning Bandits over Unknown Covariate-Shifts

Joseph Suk, Samory Kpotufe; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1114-1156

[abs][Download PDF]

Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model

Jean Tarbouriech, Matteo Pirotta, Michal Valko, Alessandro Lazaric; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1157-1178

[abs][Download PDF]

Contrastive learning, multi-view redundancy, and linear models

Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1179-1206

[abs][Download PDF]

Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data

Di Wang, Huangyu Zhang, Marco Gaboardi, Jinhui Xu; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1207-1213

[abs][Download PDF]

A case where a spindly two-layer linear network decisively outperforms any neural network with a fully connected input layer

Manfred K. Warmuth, Wojciech Kotłowski, Ehsan Amid; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1214-1236

[abs][Download PDF]

Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions

Gellért Weisz, Philip Amortila, Csaba Szepesvári; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1237-1264

[abs][Download PDF]

Non-uniform Consistency of Online Learning with Random Sampling

Changlong Wu, Narayana Santhanam; Proceedings of the 32nd International Conference on Algorithmic Learning Theory, PMLR 132:1265-1285

[abs][Download PDF]