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Apr 08, 2020
Computer Vision
Logic in Computer Science

Slicing and dicing soccer: automatic detection ofcomplex events from …

The automatic detection of events in sport videos has im-portant applications for data analytics, as well as for broadcasting andmedia companies. Thi…
Apr 08, 2020
Computer Vision
Machine Learning
Robotics

Self-Supervised Monocular Scene Flow Estimation

Scene flow estimation has been receiving increasing attention for 3D environment perception. Monocular scene flow estimation -- obtaining 3D structur…
Apr 08, 2020
Machine Learning
Computer Vision

Empirical Perspectives on One-Shot Semi-supervised Learning

One of the greatest obstacles in the adoption of deep neural networks for new applications is that training the network typically requires a large nu…
Apr 08, 2020
Machine Learning
Computer Vision

CURL: Contrastive Unsupervised Representations for Reinforcement Le…

We present CURL: Contrastive Unsupervised Representations for Reinforcement Learning. CURL extracts high-level features from raw pixels using contras…
Apr 08, 2020
Computation and Language
Machine Learning

LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compr…

BERT is a cutting-edge language representation model pre-trained by a large corpus, which achieves superior performances on various natural language …
Apr 08, 2020
Machine Learning

Solving the scalarization issues of Advantage-based Reinforcement L…

In this paper we investigate some of the issues that arise from the scalarization of the multi-objective optimization problem in the Advantage Actor …
Apr 08, 2020
Machine Learning

DeepStreamCE: A Streaming Approach to Concept Evolution Detection in …

Deep neural networks have experimentally demonstrated superior performance over other machine learning approaches in decision-making predictions. How…
Apr 08, 2020
Machine Learning
Distributed
Parallel
and Cluster Computing
Networking and Internet Architecture

In this paper, we have presented the DRL scheme for the resource management in the BFL system. We have first described the BFL system in which the blockchain network is modeled as an M/M/1 queue. Then, we have formulated the stochastic optimization …

Resource Management for Blockchain-enabled Federated Learning: A Deep…

Blockchain-enabled Federated Learning (BFL) enables model updates of Federated Learning (FL) to be stored in the blockchain in a secure and reliable …
Apr 08, 2020
Image and Video Processing
Computer Vision
Machine Learning

Time accelerated image super-resolution using shallow residual featur…

The recent advances in deep learning indicate significant progress in the field of single image super-resolution. With the advent of these techniques…
Apr 08, 2020
Computer Vision

Weakly Supervised Semantic Point Cloud Segmentation:Towards 10X Fewer…

Point cloud analysis has received much attention recently; and segmentation is one of the most important tasks. The success of existing approaches is…
Apr 08, 2020
Computer Vision

Satellite-based Prediction of Forage Conditions for Livestock in No…

This paper introduces the first dataset of satellite images labeled with forage quality by on-the-ground experts and provides proof of concept for ap…
Apr 08, 2020
Machine Learning
Neural and Evolutionary Computation

Continual Learning with Gated Incremental Memories for sequential dat…

The ability to learn in dynamic, nonstationary environments without forgetting previous knowledge, also known as Continual Learning (CL), is a key en…
Apr 08, 2020
Computation and Language

Are All Good Word Vector Spaces Isomorphic?

Existing algorithms for aligning cross-lingual word vector spaces assume that vector spaces are approximately isomorphic. As a result, they perform p…
Apr 08, 2020
Computation and Language

Self-Attention Gazetteer Embeddings for Named-Entity Recognition

Recent attempts to ingest external knowledge into neural models for named-entity recognition (NER) have exhibited mixed results. In this work, we pre…
Apr 08, 2020
Computation and Language
Machine Learning

DynaBERT: Dynamic BERT with Adaptive Width and Depth

The pre-trained language models like BERT and RoBERTa, though powerful in many natural language processing tasks, are both computational and memory e…
Apr 08, 2020
Machine Learning
Neural and Evolutionary Computation

Neural Networks Model for Travel Time Prediction Based on ODTravel Ti…

Public transportation system commuters are often interested in getting accurate travel time information to plan their daily activities. However, this…
Apr 08, 2020
Other Statistics
Machine Learning
Populations and Evolution

A machine learning methodology for real-time forecasting of the 201…

We present a timely and novel methodology that combines disease estimates from mechanistic models with digital traces, via interpretable machine-lear…
Apr 08, 2020
Computation and Language
Machine Learning

Exploiting Redundancy in Pre-trained Language Models for Efficient …

Large pre-trained contextual word representations have transformed the field of natural language processing, obtaining impressive results on a wide r…
Apr 08, 2020
Computation and Language

Transfer learning and subword sampling for asymmetric-resource one-…

There are several approaches for improving neural machine translation for low-resource languages: Monolingual data can be exploited via pretraining o…
Apr 08, 2020
Artificial Intelligence

Learning from Learners: Adapting Reinforcement Learning Agents to be …

Learning how to adapt to complex and dynamic environments is one of the most important factors that contribute to our intelligence. Endowing artifici…
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