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)

Modal-set estimation with an application to clustering AISTATS 2017
Compressed Least Squares Regression revisited AISTATS 2017
Diverse Neural Network Learns True Target Functions AISTATS 2017
Local Group Invariant Representations via Orbit Embeddings AISTATS 2017
Fast Classification with Binary Prototypes AISTATS 2017
Prediction Performance After Learning in Gaussian Process Regression AISTATS 2017
Lipschitz Density-Ratios, Structured Data, and Data-driven Tuning AISTATS 2017
Spatial Decompositions for Large Scale SVMs AISTATS 2017
Information Projection and Approximate Inference for Structured Sparse Variables AISTATS 2017
On the Interpretability of Conditional Probability Estimates in the Agnostic Setting AISTATS 2017
Efficient Online Multiclass Prediction on Graphs via Surrogate Losses AISTATS 2017
Spectral Methods for Correlated Topic Models AISTATS 2017
Label Filters for Large Scale Multilabel Classification AISTATS 2017
Learning from Conditional Distributions via Dual Embeddings AISTATS 2017
A Maximum Matching Algorithm for Basis Selection in Spectral Learning AISTATS 2017
Value-Aware Loss Function for Model-based Reinforcement Learning AISTATS 2017
Convergence Rate of Stochastic k-means AISTATS 2017
Non-Count Symmetries in Boolean & Multi-Valued Prob. Graphical Models AISTATS 2017
Scalable Greedy Feature Selection via Weak Submodularity AISTATS 2017
New bounds on the price of bandit feedback for mistake-bounded online multiclass learning ALT 2017
Minimax rates for cost-sensitive learning on manifolds with approximate nearest neighbours ALT 2017
Preference-based Teaching of Unions of Geometric Objects ALT 2017
Lifelong Learning in Costly Feature Spaces ALT 2017
Collaborative Clustering: Sample Complexity and Efficient Algorithms ALT 2017
The Complexity of Explaining Neural Networks Through (group) Invariants ALT 2017