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From Word Embeddings To Document Distances
Weight Uncertainty in Neural Network
Long Short-Term Memory Over Recursive Structures
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Learning Transferable Features with Deep Adaptation Networks
Learning Word Representations with Hierarchical Sparse Coding
DRAW: A Recurrent Neural Network For Image Generation
Unsupervised Learning of Video Representations using LSTMs
MADE: Masked Autoencoder for Distribution Estimation
Hashing for Distributed Data
Is Feature Selection Secure against Training Data Poisoning?

Mind the duality gap: safer rules for the Lasso
PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data
Generalization error bounds for learning to rank: Does the length of document lists matter?
Classification with Low Rank and Missing Data
Functional Subspace Clustering with Application to Time Series
Abstraction Selection in Model-based Reinforcement Learning
Learning Local Invariant Mahalanobis Distances
A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate
Learning from Corrupted Binary Labels via Class-Probability Estimation
On the Relationship between Sum-Product Networks and Bayesian Networks
Efficient Training of LDA on a GPU by Mean-for-Mode Estimation
A low variance consistent test of relative dependency
Streaming Sparse Principal Component Analysis
How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances?
Online Learning of Eigenvectors
Asymmetric Transfer Learning with Deep Gaussian Processes
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network
BilBOWA: Fast Bilingual Distributed Representations without Word Alignments
Strongly Adaptive Online Learning
Cascading Bandits: Learning to Rank in the Cascade Model
Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM
Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models
Multi-Task Learning for Subspace Segmentation
Convex Formulation for Learning from Positive and Unlabeled Data
Alpha-Beta Divergences Discover Micro and Macro Structures in Data
On Greedy Maximization of Entropy
The Hedge Algorithm on a Continuum
MRA-based Statistical Learning from Incomplete Rankings
A Linear Dynamical System Model for Text
HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades
Support Matrix Machines
Unsupervised Domain Adaptation by Backpropagation
The Ladder: A Reliable Leaderboard for Machine Learning Competitions
On Deep Multi-View Representation Learning
A Probabilistic Model for Dirty Multi-task Feature Selection
Deep Edge-Aware Filters