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Volume 313: Algorithmic Learning Theory, 23-26 February 2026, Fields Institute, Toronto, Canada
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Editors: Matus Telgarsky, Jonathan Ullman
Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-39
Smoothed Online Optimization for Target Tracking: Robust and Learning-Augmented Algorithms
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-36
Shallow Neural Networks Learn Low-Degree Spherical Polynomials with Feature Learning by Learnable Channel Attention
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-48
Improved Regret in Stochastic Decision-Theoretic Online Learning under Differential Privacy
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-22
PAC-Bayesian Analysis of the Surrogate Relation between Joint Embedding and Supervised Downstream Losses
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-33
Graph Inference with Effective Resistance Queries
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-31
Bridging Lifelong and Multi-Task Representation Learning: An Algorithm and a Complexity Measure
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-44
Last-iterate Convergence for Symmetric, General-sum, $2 \times 2$ Games Under The Exponential Weights Dynamic
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-38
Multi-distribution Learning: From Worst-Case Optimality to Lexicographic Min-Max Optimality
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-19
Universality of conformal prediction under the assumption of randomness
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-18
Ranking Items from Discrete Ratings: The Cost of Unknown User Thresholds
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-51
Universal Dynamic Regret and Constraint Violation Bounds for Constrained Online Convex Optimization
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-29
On the Role of Transformer Feed-Forward Layers in Nonlinear In-Context Learning
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-3
Designing Algorithms for Entropic Optimal Transport from an Optimisation Perspective
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-33
Compressibility Barriers to Neighborhood-Preserving Data Visualization
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-30
Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-19
Recycling History: Efficient Recommendations from Contextual Dueling Bandits
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-20
Optimal Bounds for Tyler’s M-Estimator for Elliptical Distributions
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-25
Large Average Subtensor Problem: Ground-State, Algorithms, and Algorithmic Barriers
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-2
A Novel Data-Dependent Learning Paradigm for Large Hypothesis Classes
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-27
How to Set $\beta_1, \beta_2$ in Adam: An Online Learning Perspective
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-16
Online Covering with Multiple Experts
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-36
Online Markov Decision Processes with Terminal Law Constraints
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-52
Vector-valued self-normalized concentration inequalities beyond sub-Gaussianity
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-31
Efficient Opportunistic Approachability
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-23
Sample Complexity Bounds for Linear Constrained MDPs with a Generative Model
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-70
Online Convex Optimization with Heavy Tails: Old Algorithms, New Regrets, and Applications
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-47
Variance Reduction and Low Sample Complexity in Stochastic Optimization via Proximal Point Method
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-25
Accelerated Mirror Descent for Non-Euclidean Star-convex Functions
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-41
No Scale Sensitive Dimension for Distribution Learning
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-27
Improved Replicable Boosting with Majority-of-Majorities
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-18
Learning with Monotone Adversarial Corruptions
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-18
Differentially Private Bilevel Optimization
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-36
DS-Compatible Log-Linear Reliability with KL-Prox EM: Monotone Ascent, Identifiability, and Generalization
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-17
The Planted Number Partitioning Problem
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-2
Optimal L2 Regularization in High-dimensional Continual Linear Regression
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-62
On Characterizations for Language Generation: Interplay of Hallucinations, Breadth, and Stability
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-49
Reusing Samples in Variance Reduction
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-52
Strategy-robust Online Learning in Contextual Pricing
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-32
Nearly Minimax Discrete Distribution Estimation in Kullback-Leibler Divergence with High Probability
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-38
Distribution-Dependent Rates for Multi-Distribution Learning
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-52
Relative Information Gain and Gaussian Process Regression
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-30
Sparse Nonparametric Contextual Bandits
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-44
Online and Offline Learning of Orderly Hypergraphs Using Queries
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-21
From Continual Learning to SGD and Back: Better Rates for Continual Linear Models
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-50
Phase Transition of Regret for Logistic Regression with Large Weights
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-28
Uniform Convergence Beyond Glivenko-Cantelli
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-21
Suspicious Alignment of SGD:A Fine-Grained Step Size Condition Analysis
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-66
On Purely Private Covariance Estimation
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-11
Sample-Near-Optimal Agnostic Boosting with Improved Running Time
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-27
Talagrand Meets Talagrand: Upper and Lower Bounds on Expected Soft Maxima of Gaussian Processes with Finite Index Sets
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-17
A Martingale Kernel Two-Sample Test
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-44
Pareto-optimal Non-uniform Language Generation
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-27
Closeness testing from distributed measurements
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-23
Privately Learning Decision Lists and a Differentially Private Winnow
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-27
Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-43
Regularized Robustly Reliable Learners
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-35
Sink equilibria and the attractors of learning in games
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-21
Beyond Discrepancy: A Closer Look at the Theory of Distribution Shift
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-19
Predictive inference for time series: why is split conformal effective despite temporal dependence?
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-24
Discriminative Feature Feedback with General Teacher Classes
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-32
Reward Selection with Noisy Observations
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-34
On the Hardness of Learning Regular Expressions
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-19
Robust Online Learning
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-14
Group-realizable multi-group learning by minimizing empirical risk
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-12
Learning from Synthetic Data: Limitations of ERM
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-23
Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-26
Convex optimization with $p$-norm oracles
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-38
Efficient and Provable Algorithms for Covariate Shift
; Proceedings of The 37th International Conference on Algorithmic Learning Theory, PMLR 313:1-34
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