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

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Papers (including subtopics)

Spectral learning of multivariate extremes JMLR 2024
Classification with Deep Neural Networks and Logistic Loss JMLR 2024
Margin-Based Active Learning of Classifiers JMLR 2024
Learning Optimal Dynamic Treatment Regimens Subject to Stagewise Risk Controls JMLR 2024
Regimes of No Gain in Multi-class Active Learning JMLR 2024
Fairness guarantees in multi-class classification with demographic parity JMLR 2024
Representation Learning via Manifold Flattening and Reconstruction JMLR 2024
Topological Node2vec: Enhanced Graph Embedding via Persistent Homology JMLR 2024
Adaptive Latent Feature Sharing for Piecewise Linear Dimensionality Reduction JMLR 2024
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks JMLR 2024
PyGOD: A Python Library for Graph Outlier Detection JMLR 2024
Neural Feature Learning in Function Space JMLR 2024
Unified Binary and Multiclass Margin-Based Classification JMLR 2024
Adjusted Wasserstein Distributionally Robust Estimator in Statistical Learning JMLR 2024
Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks JMLR 2024
Kernel Thinning JMLR 2024
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression JMLR 2024
A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment JMLR 2024
More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization JMLR 2024
Nonparametric Regression Using Over-parameterized Shallow ReLU Neural Networks JMLR 2024
Optimal Locally Private Nonparametric Classification with Public Data JMLR 2024
On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing JMLR 2024
Spherical Rotation Dimension Reduction with Geometric Loss Functions JMLR 2024
Fermat Distances: Metric Approximation, Spectral Convergence, and Clustering Algorithms JMLR 2024
Bayesian Regression Markets JMLR 2024