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)

BOBA: Byzantine-Robust Federated Learning with Label Skewness AISTATS 2024
MINTY: Rule-based models that minimize the need for imputing features with missing values AISTATS 2024
Graph Machine Learning through the Lens of Bilevel Optimization AISTATS 2024
Efficient Low-Dimensional Compression of Overparameterized Models AISTATS 2024
Unified Transfer Learning in High-Dimensional Linear Regression AISTATS 2024
Scalable Algorithms for Individual Preference Stable Clustering AISTATS 2024
Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles AISTATS 2024
When No-Rejection Learning is Consistent for Regression with Rejection AISTATS 2024
Filter, Rank, and Prune: Learning Linear Cyclic Gaussian Graphical Models AISTATS 2024
Fast and Adversarial Robust Kernelized SDU Learning AISTATS 2024
Scalable Learning of Item Response Theory Models AISTATS 2024
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models AISTATS 2024
Fair Soft Clustering AISTATS 2024
Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees AISTATS 2024
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels AISTATS 2024
Intrinsic Gaussian Vector Fields on Manifolds AISTATS 2024
MMD-based Variable Importance for Distributional Random Forest AISTATS 2024
Adaptive Discretization for Event PredicTion (ADEPT) AISTATS 2024
Importance Matching Lemma for Lossy Compression with Side Information AISTATS 2024
Confident Feature Ranking AISTATS 2024
Transductive conformal inference with adaptive scores AISTATS 2024
Learning Latent Partial Matchings with Gumbel-IPF Networks AISTATS 2024
Integrating Uncertainty Awareness into Conformalized Quantile Regression AISTATS 2024
Estimation of partially known Gaussian graphical models with score-based structural priors AISTATS 2024
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes AISTATS 2024