conftrace_

Core Methods

48,729 papers (8 classified directly here)

Subtopics

Representation Learning (20,822) Classification (15,805) Regression (5,004) Embedding Learning (3,753) Clustering (3,638) Metric Learning (2,854) Graph Neural Networks (1,141) Graphical Models (985) Feature Learning (860) Dimensionality Reduction (707) Kernel Methods (642) Interpretability (499) Feature Selection (479) Matrix Factorization (383) Ranking (283) Ensemble Methods (267) Anomaly Detection (267) Support Vector Machine (254) Sequence Modeling (237) Structured Prediction (205) Sequence Labeling (166) Topic Modeling (123) Sparse Coding (107) Matrix Completion (103) Retrieval (99) Neural Networks (79) Inference (21) Model Selection (19) Decision Tree (16) Prediction (15) Density Estimation (9) Estimation (8) Feature Extraction (7) Information Extraction (7)

Papers per year

4
48
348
949
4892
4576
'00
'05
'10
'15
'20
'25

Papers (including subtopics)

Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent AISTATS 2024
Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers AISTATS 2024
EM for Mixture of Linear Regression with Clustered Data AISTATS 2024
Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity AISTATS 2024
Approximate Leave-one-out Cross Validation for Regression with $\ell_1$ Regularizers AISTATS 2024
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels AISTATS 2024
An Impossibility Theorem for Node Embedding AISTATS 2024
Mixed variational flows for discrete variables AISTATS 2024
Multi-Resolution Active Learning of Fourier Neural Operators AISTATS 2024
Functional Graphical Models: Structure Enables Offline Data-Driven Optimization AISTATS 2024
Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective AISTATS 2024
Learning Adaptive Kernels for Statistical Independence Tests AISTATS 2024
Learning Cartesian Product Graphs with Laplacian Constraints AISTATS 2024
Bayesian Online Learning for Consensus Prediction AISTATS 2024
Efficient Data Shapley for Weighted Nearest Neighbor Algorithms AISTATS 2024
BlockBoost: Scalable and Efficient Blocking through Boosting AISTATS 2024
Maximum entropy GFlowNets with soft Q-learning AISTATS 2024
Large-Scale Gaussian Processes via Alternating Projection AISTATS 2024
Graph fission and cross-validation AISTATS 2024
Graph Pruning for Enumeration of Minimal Unsatisfiable Subsets AISTATS 2024
On Parameter Estimation in Deviated Gaussian Mixture of Experts AISTATS 2024
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts AISTATS 2024
From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach AISTATS 2024
Adaptive and non-adaptive minimax rates for weighted Laplacian-Eigenmap based nonparametric regression AISTATS 2024
Deep Dependency Networks and Advanced Inference Schemes for Multi-Label Classification AISTATS 2024