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)

Visual Reference Resolution using Attention Memory for Visual Dialog NIPS 2017
Testing and Learning on Distributions with Symmetric Noise Invariance NIPS 2017
Learning Overcomplete HMMs NIPS 2017
Masked Autoregressive Flow for Density Estimation NIPS 2017
Learning with Average Top-k Loss NIPS 2017
Max-Margin Invariant Features from Transformed Unlabelled Data NIPS 2017
Label Distribution Learning Forests NIPS 2017
Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation NIPS 2017
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding NIPS 2017
Discriminative State Space Models NIPS 2017
Generalizing GANs: A Turing Perspective NIPS 2017
A Screening Rule for l1-Regularized Ising Model Estimation NIPS 2017
VAIN: Attentional Multi-agent Predictive Modeling NIPS 2017
Sobolev Training for Neural Networks NIPS 2017
Context Selection for Embedding Models NIPS 2017
Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes NIPS 2017
Neural Discrete Representation Learning NIPS 2017
A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning NIPS 2017
Thy Friend is My Friend: Iterative Collaborative Filtering for Sparse Matrix Estimation NIPS 2017
Positive-Unlabeled Learning with Non-Negative Risk Estimator NIPS 2017
Group Sparse Additive Machine NIPS 2017
From Parity to Preference-based Notions of Fairness in Classification NIPS 2017
Nonparametric Online Regression while Learning the Metric NIPS 2017
Working hard to know your neighbor's margins: Local descriptor learning loss NIPS 2017
Hiding Images in Plain Sight: Deep Steganography NIPS 2017