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Volume 272: Algorithmic Learning Theory, 24-27 February 2025, Politecnico di Milano, Milan, Italy
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Editors: Gautam Kamath, Po-Ling Loh
Algorithmic Learning Theory 2025: Preface
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1-3
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When and why randomised exploration works (in linear bandits)
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:4-22
Generalization bounds for mixing processes via delayed online-to-PAC conversions
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:23-40
Agnostic Private Density Estimation for GMMs via List Global Stability
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:41-66
Refining the Sample Complexity of Comparative Learning
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:67-88
Understanding Aggregations of Proper Learners in Multiclass Classification
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:89-111
Proper Learnability and the Role of Unlabeled Data
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:112-133
Sample Compression Scheme Reductions
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:134-162
Strategyproof Learning with Advice
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:163-166
Cost-Free Fairness in Online Correlation Clustering
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:167-203
Non-stochastic Bandits With Evolving Observations
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:204-227
Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:228-245
A Model for Combinatorial Dictionary Learning and Inference
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:246-288
Differentially Private Multi-Sampling from Distributions
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:289-314
Near-Optimal Rates for O(1)-Smooth DP-SCO with a Single Epoch and Large Batches
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:315-348
Generalisation under gradient descent via deterministic PAC-Bayes
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:349-389
Boosting, Voting Classifiers and Randomized Sample Compression Schemes
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:390-404
Effective Littlestone dimension
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:405-417
Is Transductive Learning Equivalent to PAC Learning?
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:418-443
Full Swap Regret and Discretized Calibration
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:444-480
A PAC-Bayesian Link Between Generalisation and Flat Minima
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:481-511
Reliable Active Apprenticeship Learning
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:512-538
For Universal Multiclass Online Learning, Bandit Feedback and Full Supervision are Equivalent
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:539-559
A Complete Characterization of Learnability for Stochastic Noisy Bandits
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:560-577
Efficient Optimal PAC Learning
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:578-580
Do PAC-Learners Learn the Marginal Distribution?
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:581-610
Optimal and learned algorithms for the online list update problem with Zipfian accesses
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:611-648
Information-Theoretic Guarantees for Recovering Low-Rank Tensors from Symmetric Rank-One Measurements
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:649-652
Sharp bounds on aggregate expert error
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:653-663
Quantile Multi-Armed Bandits with 1-bit Feedback
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:664-699
On the Hardness of Learning One Hidden Layer Neural Networks
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:700-701
Minimax-optimal and Locally-adaptive Online Nonparametric Regression
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:702-735
Error dynamics of mini-batch gradient descent with random reshuffling for least squares regression
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:736-770
Computationally efficient reductions between some statistical models
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:771-771
Enhanced $H$-Consistency Bounds
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:772-813
Center-Based Approximation of a Drifting Distribution
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:814-845
Fast Convergence of $Φ$-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:846-869
A Characterization of List Regression
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:870-920
On Generalization Bounds for Neural Networks with Low Rank Layers
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:921-936
Data Dependent Regret Bounds for Online Portfolio Selection with Predicted Returns
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:937-984
A Unified Theory of Supervised Online Learnability
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:985-1007
An Online Feasible Point Method for Benign Generalized Nash Equilibrium Problems.
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1008-1040
The Dimension Strikes Back with Gradients: Generalization of Gradient Methods in Stochastic Convex Optimization
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1041-1107
Efficient PAC Learning of Halfspaces with Constant Malicious Noise Rate
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1108-1137
Self-Directed Node Classification on Graphs
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1138-1168
High-accuracy sampling from constrained spaces with the Metropolis-adjusted Preconditioned Langevin Algorithm
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1169-1220
Clustering with bandit feedback: breaking down the computation/information gap
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1221-1284
Online Learning of Quantum States with Logarithmic Loss via VB-FTRL
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1285-1312
Noisy Computing of the Threshold Function
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1313-1315
How rotation invariant algorithms are fooled by noise on sparse targets
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1316-1360
Logarithmic Regret for Unconstrained Submodular Maximization Stochastic Bandit
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1361-1385
The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis
; Proceedings of The 36th International Conference on Algorithmic Learning Theory, PMLR 272:1386-1387
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