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01/06/2021
Interspeech 2021 Deep Noise Suppression Challenge
The Deep Noise Suppression (DNS) challenge is designed to foster innovat...
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11/23/2020
Resonance: Replacing Software Constants with Context-Aware Models in Real-time Communication
Large software systems tune hundreds of 'constants' to optimize their ru...
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09/10/2020
ICASSP 2021 Acoustic Echo Cancellation Challenge: Datasets and Testing Framework
The ICASSP 2021 Acoustic Echo Cancellation Challenge is intended to stim...
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07/29/2020
DNN No-Reference PSTN Speech Quality Prediction
Classic public switched telephone networks (PSTN) are often a black box ...
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05/16/2020
The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Testing Framework, and Challenge Results
The INTERSPEECH 2020 Deep Noise Suppression (DNS) Challenge is intended ...
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01/23/2020
The INTERSPEECH 2020 Deep Noise Suppression Challenge: Datasets, Subjective Speech Quality and Testing Framework
The INTERSPEECH 2020 Deep Noise Suppression Challenge is intended to pro...
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01/16/2020
Estimating Aggregate Properties In Relational Networks With Unobserved Data
Aggregate network properties such as cluster cohesion and the number of ...
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09/17/2019
A scalable noisy speech dataset and online subjective test framework
Background noise is a major source of quality impairments in Voice over ...
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08/26/2019
OpenSpiel: A Framework for Reinforcement Learning in Games
OpenSpiel is a collection of environments and algorithms for research in...
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10/21/2018
Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
Optimization of parameterized policies for reinforcement learning (RL) i...
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09/13/2018
A Fairness-aware Hybrid Recommender System
Recommender systems are used in variety of domains affecting people's li...
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03/06/2017
Neural Episodic Control
Deep reinforcement learning methods attain super-human performance in a ...
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06/06/2016
Unifying Count-Based Exploration and Intrinsic Motivation
We consider an agent's uncertainty about its environment and the problem...
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04/16/2016
DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression
Scaling multinomial logistic regression to datasets with very large numb...
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10/16/2014
