Home     
Get started
Latest Conferences Popular
VISION
LANGUAGE
SOUND
ROBOTICS
OPTICS
GENOMICS
May 24, 2018
Optimization and Control
Distributed
Parallel
and Cluster Computing
Machine Learning

We prove convergence of local SGD and are the first to show that local SGD attains linear as speed-up when parallelized among K workers. We show that local SGD saves up to a factor of O(T1/2) in global communication rounds compared to mini-batch S...

Local SGD Converges Fast and Communicates Little

Mini-batch stochastic gradient descent (SGD) is the state of the art in large scale parallel machine learning, but its scalability is limited by a ...
May 24, 2018
By acharya
Data Structures and Algorithms
Artificial Intelligence
Machine Learning

We would like to thank Vasant Honavar who told us about the problems considered here and for several helpful discussions that were essential for us to complete this work.

Learning and Testing Causal Models with Interventions

We consider testing and learning problems on causal Bayesian networks as defined by Pearl (Pearl, 2009). Given a causal Bayesian network $\mathcal{...
May 24, 2018
Computer Vision
Graphics

Stereo Magnification: Learning View Synthesis using Multiplane Images

The view synthesis problem--generating novel views of a scene from known imagery--has garnered recent attention due in part to compelling applicati...
May 24, 2018
Machine Learning

Implicit Autoencoders

In this paper, we describe the "implicit autoencoder" (IAE), a generative autoencoder in which both the generative path and the recognition path ar...
May 24, 2018
Machine Learning
Artificial Intelligence

Meta-Gradient Reinforcement Learning

The goal of reinforcement learning algorithms is to estimate and/or optimise the value function. However, unlike supervised learning, no teacher or...
May 24, 2018
By sharanv
Machine Learning

New Insights into Bootstrapping for Bandits

We investigate the use of bootstrapping in the bandit setting. We first show that the commonly used non-parametric bootstrapping (NPB) procedure ca...
May 24, 2018
By caglarg
Neural and Evolutionary Computation

Hyperbolic Attention Networks

We introduce hyperbolic attention networks to endow neural networks with enough capacity to match the complexity of data with hierarchical and powe...
May 24, 2018
Artificial Intelligence
Computation and Language
Information Retrieval

Mining Procedures from Technical Support Documents

Guided troubleshooting is an inherent task in the domain of technical support services. When a customer experiences an issue with the functioning o...
May 24, 2018
Computer Vision

Mobile Face Tracking: A Survey and Benchmark

With the rapid development of smartphones, facial analysis has been playing an increasingly important role in a multitude of mobile applications. I...
May 24, 2018
Cryptography and Security

Detecting Homoglyph Attacks with a Siamese Neural Network

A homoglyph (name spoofing) attack is a common technique used by adversaries to obfuscate file and domain names. This technique creates process or ...
May 24, 2018
Computer Vision

Image-to-image translation for cross-domain disentanglement

Deep image translation methods have recently shown excellent results, outputting high-quality images covering multiple modes of the data distributi...
May 24, 2018
By leead
Machine Learning
Computational Complexity
Computational Geometry

Learning convex polytopes with margin

We present a near-optimal algorithm for properly learning convex polytopes in the realizable PAC setting from data with a margin. Our first contrib...
May 24, 2018
By mathieu
Machine Learning

Learning Classifiers with Fenchel-Young Losses: Generalized Entropi...

We study in this paper Fenchel-Young losses, a generic way to construct convex loss functions from a convex regularizer. We provide an in-depth stu...
May 24, 2018
By ylu25
Neural and Evolutionary Computation

Autonomously and Simultaneously Refining Deep Neural Network Parame...

The choice of parameters, and the design of the network architecture are important factors affecting the performance of deep neural networks. Howev...
May 24, 2018
Computer Vision

Jointly Optimize Data Augmentation and Network Training: Adversaria...

Random data augmentation is a critical technique to avoid overfitting in training deep neural network models. However, data augmentation and networ...
May 24, 2018
Computer Vision
Artificial Intelligence
Computation and Language
Machine Learning
Multimedia

R-VQA: Learning Visual Relation Facts with Semantic Attention for V...

Recently, Visual Question Answering (VQA) has emerged as one of the most significant tasks in multimodal learning as it requires understanding both...
May 24, 2018
By ters
Machine Learning
Artificial Intelligence
Neural and Evolutionary Computation

Been There, Done That: Meta-Learning with Episodic Recall

Meta-learning agents excel at rapidly learning new tasks from open-ended task distributions; yet, they forget what they learn about each task as so...
May 24, 2018
Computer Vision

LF-Net: Learning Local Features from Images

We present a novel deep architecture and a training strategy to learn a local feature pipeline from scratch, using collections of images without th...
May 24, 2018
By shkim
Machine Learning

Uncertainty-Aware Attention for Reliable Interpretation and Prediction

Attention mechanism is effective in both focusing the deep learning models on relevant features and interpreting them. However, attentions may be u...
May 24, 2018
Robotics
Multiagent Systems
Systems and Control

Decentralized MPC based Obstacle Avoidance for Multi-Robot Target ...

In this work, we consider the problem of decentralized multi-robot target tracking and obstacle avoidance in dynamic environments. Each robot execu...
There aren't more projects

Every arXiv paper needs to be discussed

You’re adding your first comment!
How to quickly get a good reply:
  • Offer a constructive comment on the author work.
  • Add helpful links to code implementation or project page.