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NeurIPS 2023 accepted papers on Learning theory and algorithms

426 of the 3,584 papers accepted at NeurIPS 2023 (11.9%) are on Learning theory and algorithms, compared with 14.0% at NeurIPS 2022. They fall into 9 topics.

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Topics and papers

Prediction and decision losses · 96 papers

When Do Neural Nets Outperform Boosted Trees on Tabular Data? (72 citations)
Explaining Predictive Uncertainty with Information Theoretic Shapley Values (14 citations)
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation (9 citations)
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning (7 citations)
Data Pruning via Moving-one-Sample-out (6 citations)
Human-Aligned Calibration for AI-Assisted Decision Making (6 citations)
Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach (5 citations)
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance (4 citations)
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models (4 citations)
Joint Training of Deep Ensembles Fails Due to Learner Collusion (4 citations)
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities (4 citations)
UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition (4 citations)

and 84 more in the interactive map.

Sample complexity · 91 papers

On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions (19 citations)
Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints (8 citations)
Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing (4 citations)
Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach (4 citations)
Distributionally Robust Linear Quadratic Control (4 citations)
Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs (4 citations)
Optimal approximation using complex-valued neural networks (3 citations)
Private estimation algorithms for stochastic block models and mixture models (3 citations)
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity (3 citations)
A Theory of Unsupervised Translation Motivated by Understanding Animal Communication (2 citations)
Accelerating Value Iteration with Anchoring (2 citations)
Faster Relative Entropy Coding with Greedy Rejection Coding (2 citations)

and 79 more in the interactive map.

Kernels and regression theory · 55 papers

Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection (15 citations)
A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning (7 citations)
A unified framework for information-theoretic generalization bounds (7 citations)
High-dimensional Asymptotics of Denoising Autoencoders (6 citations)
Universality laws for Gaussian mixtures in generalized linear models (6 citations)
A Spectral Theory of Neural Prediction and Alignment (5 citations)
Koopman Kernel Regression (5 citations)
MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting (4 citations)
Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives (4 citations)
Sharp Spectral Rates for Koopman Operator Learning (4 citations)
Statistical Insights into HSIC in High Dimensions (4 citations)
Estimating Koopman operators with sketching to provably learn large scale dynamical systems (3 citations)

and 43 more in the interactive map.

Matrix and tensor methods · 43 papers

Fast Attention Requires Bounded Entries (9 citations)
Clifford Group Equivariant Neural Networks (8 citations)
Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems (5 citations)
Conformalized matrix completion (3 citations)
Horospherical Decision Boundaries for Large Margin Classification in Hyperbolic Space (3 citations)
A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing (2 citations)
An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions (2 citations)
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition (2 citations)
Optimal Preconditioning and Fisher Adaptive Langevin Sampling (2 citations)
Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent (2 citations)
Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares (2 citations)
Robust covariance estimation with missing values and cell-wise contamination (2 citations)

and 31 more in the interactive map.

Combinatorial and search optimization · 35 papers

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization (24 citations)
DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization (23 citations)
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks (11 citations)
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNets (10 citations)
Macro Placement by Wire-Mask-Guided Black-Box Optimization (10 citations)
Rigorous Runtime Analysis of MOEA/D for Solving Multi-Objective Minimum Weight Base Problems (8 citations)
Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete (6 citations)
Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective (5 citations)
A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability (4 citations)
DESSERT: An Efficient Algorithm for Vector Set Search with Vector Set Queries (4 citations)
Neural Lyapunov Control for Discrete-Time Systems (4 citations)
Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions (4 citations)

and 23 more in the interactive map.

Submodular and game algorithms · 31 papers

A Scalable Neural Network for DSIC Affine Maximizer Auction Design (6 citations)
Supply-Side Equilibria in Recommender Systems (6 citations)
Data Market Design through Deep Learning (4 citations)
Fair Allocation of Indivisible Chores: Beyond Additive Costs (3 citations)
A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games (2 citations)
Core-sets for Fair and Diverse Data Summarization (2 citations)
Mode Connectivity in Auction Design (2 citations)
Anonymous and Copy-Robust Delegations for Liquid Democracy (1 citation)
Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling (1 citation)
Computing Optimal Nash Equilibria in Multiplayer Games (1 citation)
Dynamic Non-monotone Submodular Maximization (1 citation)
Learning Regularized Monotone Graphon Mean-Field Games (1 citation)

and 19 more in the interactive map.

Clustering · 31 papers

A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective (23 citations)
Orthogonal Non-negative Tensor Factorization based Multi-view Clustering (15 citations)
Fast and Simple Spectral Clustering in Theory and Practice (4 citations)
Exact recovery and Bregman hard clustering of node-attributed Stochastic Block Model (2 citations)
Large sample spectral analysis of graph-based multi-manifold clustering (2 citations)
Replicable Clustering (2 citations)
Single-Pass Pivot Algorithm for Correlation Clustering. Keep it simple! (2 citations)
Fast Approximation of Similarity Graphs with Kernel Density Estimation (1 citation)
Fully Dynamic $k$-Clustering in $\tilde O(k)$ Update Time (1 citation)
Multi-Swap k-Means++ (1 citation)
Near-Optimal $k$-Clustering in the Sliding Window Model (1 citation)
Recovering Unbalanced Communities in the Stochastic Block Model with Application to Clustering with a Faulty Oracle (1 citation)

and 19 more in the interactive map.

Fairness · 28 papers

Scalable Fair Influence Maximization (5 citations)
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach (4 citations)
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions (3 citations)
Causal Fairness for Outcome Control (3 citations)
Equal Opportunity of Coverage in Fair Regression (3 citations)
Fair Canonical Correlation Analysis (3 citations)
FairLISA: Fair User Modeling with Limited Sensitive Attributes Information (3 citations)
Fairness Aware Counterfactuals for Subgroups (3 citations)
Adapting Fairness Interventions to Missing Values (2 citations)
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness (2 citations)
Counterfactually Fair Representation (2 citations)
Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors (2 citations)

and 16 more in the interactive map.

Optimal transport · 16 papers

and 4 more in the interactive map.

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