My Selected papers from NIPS 2018 (Neurips’18)
This article is originally published at https://hameddaily.blogspot.com/
I attended NIPS’18 in Montreal and here is the list of papers that I found interesting from the talks and poster sessions:
Generatives And Adverserial:
GILBO: One Metric to Measure Them All
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
Assessing Generative Models via Precision and Recall
With Friends Like These, Who Needs Adversaries?
Generalizing to Unseen Domains via Adversarial Data Augmentation
Multimodal Generative Models for Scalable Weakly-Supervised Learning
SGD and optimization
cpSGD: Communication-efficient and differentially-private distributed SGD
How Does Batch Normalization Help Optimization?
Visualizing the Loss Landscape of Neural Nets
The Lingering of Gradients: How to Reuse Gradients Over Time
Uniform Convergence of Gradients for Non-Convex Learning and Optimization
Adaptive Methods for Nonconvex Optimization
Distributed Stochastic Optimization via Adaptive SGD
Speech
Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices
Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
Language Modeling
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking
Others:
A Game-Theoretic Approach to Recommendation Systems with Strategic Content Providers
On the Dimensionality of Word Embedding
Gaussian Process Prior Variational Autoencoders
Hierarchical Graph Representation Learning with Differentiable Pooling
Sanity Checks for Saliency Maps
Minimax Statistical Learning with Wasserstein distances
The Global Anchor Method for Quantifying Linguistic Shifts and Domain Adaptation
Blockwise Parallel Decoding for Deep Autoregressive Models
Improving Simple Models with Confidence Profiles
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