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#1
Introduction to Reinforcement Learning with Function Approximation
#2
Deep Learning
#3
Monte Carlo Inference Methods
#4
Large-Scale Distributed Systems for Training Neural Networks
#5
Competitive Distribution Estimation: Why is Good-Turing Good
#6
Probabilistic Machine Learning: Foundations and Frontiers
#7
DIANNE - Distributed Artificial Neural Networks
#8
Fast Convergence of Regularized Learning in Games
#9
Interactive Control of Diverse Complex Characters with Neural Networks
#10
An interactive system for the extraction of meaningful visualizations from high-dimensional data
#11
Deep Learning using Approximate Hardware
#12
Incremental Methods for Additive Cost Convex Optimization
#13
Probabilistic Line Searches for Stochastic Optimization
#14
COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
#15
Automatic Variational Inference in Stan
#16
The Human Kernel
#17
Computational Principles for Deep Neuronal Architectures
#18
End-To-End Memory Networks
#19
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
#20
Deep Visual Analogy-Making
#21
Diagnosis and Therapy of Psychiatric Disorders Based on Brain Dynamics
#22
Training Very Deep Networks
#23
Post-selection Inference for Forward Stepwise Regression, Lasso and other Adaptive Statistical procedures
#24
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
#25
Attention-Based Models for Speech Recognition
#26
Precision-Recall-Gain Curves: PR Analysis Done Right
#27
Accelerated Deep Learning on GPUs: From Large Scale Training to Embedded Deployment
#28
End-To-End Memory Networks
#29
Training Very Deep Networks
#30
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
#31
Learning Wake-Sleep Recurrent Attention Models
#32
Pointer Networks
#33
Attention-Based Models for Speech Recognition
#34
Deep Convolutional Inverse Graphics Network
#35
Action-Conditional Video Prediction using Deep Networks in Atari Games
#36
Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation
#37
Adaptive Online Learning
#38
A Reduced-Dimension fMRI Shared Response Model
#39
Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets
#40
Learning with Intelligent Teacher: Similarity Control and Knowledge Transfer
#41
Deep Learning Symposium
#42
Brains, Minds and Machines
#43
Less is More: Nyström Computational Regularization
#44
Active Learning from Weak and Strong Labelers
#45
Algorithms Among Us: the Societal Impacts of Machine Learning
#46
Deep Reinforcement Learning
#47
Machine Learning For Healthcare (MLHC)
#48
Reasoning, Attention, Memory (RAM) Workshop
#49
Quantum Machine Learning
#50
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