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)

Practical Data-Dependent Metric Compression with Provable Guarantees NIPS 2017
Partial Hard Thresholding: Towards A Principled Analysis of Support Recovery NIPS 2017
Selective Classification for Deep Neural Networks NIPS 2017
Learning to See Physics via Visual De-animation NIPS 2017
Adversarial Symmetric Variational Autoencoder NIPS 2017
Action Centered Contextual Bandits NIPS 2017
Cost efficient gradient boosting NIPS 2017
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models NIPS 2017
A Meta-Learning Perspective on Cold-Start Recommendations for Items NIPS 2017
Deep Hyperspherical Learning NIPS 2017
Interpretable and Globally Optimal Prediction for Textual Grounding using Image Concepts NIPS 2017
Unbiased estimates for linear regression via volume sampling NIPS 2017
Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces NIPS 2017
Variable Importance Using Decision Trees NIPS 2017
Regret Analysis for Continuous Dueling Bandit NIPS 2017
Poincaré Embeddings for Learning Hierarchical Representations NIPS 2017
A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening NIPS 2017
Cross-Spectral Factor Analysis NIPS 2017
Inductive Representation Learning on Large Graphs NIPS 2017
Improved Graph Laplacian via Geometric Self-Consistency NIPS 2017
Predictive-State Decoders: Encoding the Future into Recurrent Networks NIPS 2017
Practical Hash Functions for Similarity Estimation and Dimensionality Reduction NIPS 2017
Gaussian Quadrature for Kernel Features NIPS 2017
LightGBM: A Highly Efficient Gradient Boosting Decision Tree NIPS 2017
The Neural Hawkes Process: A Neurally Self-Modulating Multivariate Point Process NIPS 2017