AAAI 2024 accepted papers on Learning theory and algorithms
291 of the 2,864 papers accepted at AAAI 2024 (10.2%) are on Learning theory and algorithms, compared with 11.3% at AAAI 2023. They fall into 9 topics.
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Topics and papers
Combinatorial and search optimization · 87 papers
- NN-Steiner: A Mixed Neural-Algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem (11 citations)
- Adaptive Reactive Synthesis for LTL and LTLf Modulo Theories (10 citations)
- Towards Running Time Analysis of Interactive Multi-Objective Evolutionary Algorithms (10 citations)
- How to Use the Metropolis Algorithm for Multi-Objective Optimization? (9 citations)
- Neural Closure Certificates (7 citations)
- Optimal Survival Trees: A Dynamic Programming Approach (7 citations)
- Abstract Action Scheduling for Optimal Temporal Planning via OMT (6 citations)
- E2E-AT: A Unified Framework for Tackling Uncertainty in Task-Aware End-to-End Learning (6 citations)
- Robust Beamforming for Downlink Multi-Cell Systems: A Bilevel Optimization Perspective (6 citations)
- Taming Binarized Neural Networks and Mixed-Integer Programs (6 citations)
- DeepSaDe: Learning Neural Networks That Guarantee Domain Constraint Satisfaction (5 citations)
- Learning to Learn in Interactive Constraint Acquisition (5 citations)
and 75 more in the interactive map.
Prediction and decision losses · 66 papers
- Shaping Up SHAP: Enhancing Stability through Layer-Wise Neighbor Selection (18 citations)
- Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles (16 citations)
- Integrated Decision Gradients: Compute Your Attributions Where the Model Makes Its Decision (16 citations)
- Symbolic Regression Enhanced Decision Trees for Classification Tasks (15 citations)
- The Evidence Contraction Issue in Deep Evidential Regression: Discussion and Solution (14 citations)
- Variable Importance in High-Dimensional Settings Requires Grouping (14 citations)
- Uncertainty Regularized Evidential Regression (13 citations)
- Delivering Inflated Explanations (11 citations)
- Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize (11 citations)
- Quantile-Regression-Ensemble: A Deep Learning Algorithm for Downscaling Extreme Precipitation (11 citations)
- Generalization Analysis of Machine Learning Algorithms via the Worst-Case Data-Generating Probability Measure (10 citations)
- Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems (10 citations)
and 54 more in the interactive map.
Submodular and game algorithms · 53 papers
- Mixed Fair Division: A Survey (12 citations)
- On Optimal Tradeoffs between EFX and Nash Welfare (12 citations)
- Almost Envy-Free Allocations of Indivisible Goods or Chores with Entitlements (7 citations)
- Proportional Aggregation of Preferences for Sequential Decision Making (7 citations)
- Competition among Pairwise Lottery Contests (6 citations)
- Pay to (Not) Play: Monetizing Impatience in Mobile Games (6 citations)
- Proportional Representation in Metric Spaces and Low-Distortion Committee Selection (6 citations)
- Information Design for Congestion Games with Unknown Demand (5 citations)
- Maximizing Nash Social Welfare under Two-Sided Preferences (5 citations)
- Repeated Fair Allocation of Indivisible Items (5 citations)
- Temporal Fairness in Multiwinner Voting (5 citations)
- Weighted Envy-Freeness for Submodular Valuations (5 citations)
and 41 more in the interactive map.
Fairness · 30 papers
- Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification (18 citations)
- A Sequentially Fair Mechanism for Multiple Sensitive Attributes (9 citations)
- Intra- and Inter-group Optimal Transport for User-Oriented Fairness in Recommender Systems (8 citations)
- Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation (8 citations)
- Manipulation-Robust Selection of Citizens’ Assemblies (7 citations)
- Promoting Fair Vaccination Strategies through Influence Maximization: A Case Study on COVID-19 Spread (7 citations)
- Fairness with Censorship: Bridging the Gap between Fairness Research and Real-World Deployment (5 citations)
- Preventing Eviction-Caused Homelessness through ML-Informed Distribution of Rental Assistance (5 citations)
- Fair Lotteries for Participatory Budgeting (4 citations)
- Long-Term Fair Decision Making through Deep Generative Models (4 citations)
- Strategyproof Mechanisms for Group-Fair Obnoxious Facility Location Problems (4 citations)
- The Fairness Fair: Bringing Human Perception into Collective Decision-Making (4 citations)
and 18 more in the interactive map.
Clustering · 22 papers
- Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding (109 citations)
- Decoupled Contrastive Multi-View Clustering with High-Order Random Walks (92 citations)
- Learning Cluster-Wise Anchors for Multi-View Clustering (68 citations)
- Sample-Level Cross-View Similarity Learning for Incomplete Multi-View Clustering (42 citations)
- Low-Rank Kernel Tensor Learning for Incomplete Multi-View Clustering (35 citations)
- Deep Variational Incomplete Multi-View Clustering: Exploring Shared Clustering Structures (28 citations)
- DVSAI: Diverse View-Shared Anchors Based Incomplete Multi-View Clustering (24 citations)
- Discriminatively Fuzzy Multi-View K-means Clustering with Local Structure Preserving (11 citations)
- Parameterized Approximation Algorithms for Sum of Radii Clustering and Variants (9 citations)
- Big Learning Expectation Maximization (5 citations)
- Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with Outliers (5 citations)
- Low-Distortion Clustering with Ordinal and Limited Cardinal Information (4 citations)
and 10 more in the interactive map.
Matrix and tensor methods · 10 papers
- Towards Multi-Mode Outlier Robust Tensor Ring Decomposition (9 citations)
- LERE: Learning-Based Low-Rank Matrix Recovery with Rank Estimation (5 citations)
- Secure Distributed Sparse Gaussian Process Models Using Multi-Key Homomorphic Encryption (4 citations)
- Delegation-Relegation for Boolean Matrix Factorization (1 citation)
- Efficient Learning of PDEs via Taylor Expansion and Sparse Decomposition into Value and Fourier Domains (1 citation)
- Exploiting Data Geometry in Machine Learning (1 citation)
- Iterative Regularization with k-support Norm: An Important Complement to Sparse Recovery (1 citation)
- Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions (1 citation)
- Superposed Atomic Representation for Robust High-Dimensional Data Recovery of Multiple Low-Dimensional Structures (1 citation)
- The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank
Optimal transport · 8 papers
- Hierarchical Multi-Marginal Optimal Transport for Network Alignment (15 citations)
- An Optimal Transport View for Subspace Clustering and Spectral Clustering (6 citations)
- Double-Bounded Optimal Transport for Advanced Clustering and Classification (5 citations)
- Learning Ultrametric Trees for Optimal Transport Regression (2 citations)
- Optimal Transport with Cyclic Symmetry (2 citations)
- A Novel Skip Orthogonal List for Dynamic Optimal Transport Problem (1 citation)
- Optimal Transport with Tempered Exponential Measures (1 citation)
- A Class of Topological Pseudodistances for Fast Comparison of Persistence Diagrams
Kernels and regression theory · 8 papers
- Improving Neural Network Generalization on Data-Limited Regression with Doubly-Robust Boosting (12 citations)
- Lost Domain Generalization Is a Natural Consequence of Lack of Training Domains (5 citations)
- Double-Descent Curves in Neural Networks: A New Perspective Using Gaussian Processes (4 citations)
- High-Dimensional Analysis for Generalized Nonlinear Regression: From Asymptotics to Algorithm (3 citations)
- TMPNN: High-Order Polynomial Regression Based on Taylor Map Factorization (3 citations)
- Multi-View Randomized Kernel Classification via Nonconvex Optimization (1 citation)
- Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data
- Understanding Surprising Generalization Phenomena in Deep Learning
Sample complexity · 7 papers
- Robust Nonparametric Regression under Poisoning Attack (8 citations)
- Learning Broadcast Protocols (4 citations)
- Complexity of Neural Network Training and ETR: Extensions with Effectively Continuous Functions (3 citations)
- Efficient Algorithms for Non-gaussian Single Index Models with Generative Priors (3 citations)
- Testing Self-Reducible Samplers (2 citations)
- Identification for Tree-Shaped Structural Causal Models in Polynomial Time (1 citation)
- Sampling for Beyond-Worst-Case Online Ranking