
Markov Game with Switching Costs
We study a general Markov game with metric switching costs: in each roun...
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Discrete Autoregressive Variational Attention Models for Text Modeling
Variational autoencoders (VAEs) have been widely applied for text modeli...
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Simple Combinatorial Algorithms for Combinatorial Bandits: Corruptions and Approximations
We consider the stochastic combinatorial semibandit problem with advers...
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Graph Symbiosis Learning
We introduce a framework for learning from multiple generated graph view...
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Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model
Inspired by biological evolution, we explain the rationality of Vision T...
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NASBERT: TaskAgnostic and AdaptiveSize BERT Compression with Neural Architecture Search
While pretrained language models (e.g., BERT) have achieved impressive ...
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Differential Privacy for Pairwise Learning: Nonconvex Analysis
Pairwise learning focuses on learning tasks with pairwise loss functions...
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Design and Control of a Highly Redundant RigidFlexible Coupling Robot to Assist the COVID19 OropharyngealSwab Sampling
The outbreak of novel coronavirus pneumonia (COVID19) has caused mortal...
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ReturnBased Contrastive Representation Learning for Reinforcement Learning
Recently, various auxiliary tasks have been proposed to accelerate repre...
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StragglerResilient Distributed Machine Learning with Dynamic Backup Workers
With the increasing demand for largescale training of machine learning ...
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On the quantization of recurrent neural networks
Integer quantization of neural networks can be defined as the approximat...
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Learning Augmented Index Policy for Optimal Service Placement at the Network Edge
We consider the problem of service placement at the network edge, in whi...
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Distributed Stochastic Consensus Optimization with Momentum for Nonconvex Nonsmooth Problems
While many distributed optimization algorithms have been proposed for so...
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TensorFlow Lite Micro: Embedded Machine Learning on TinyML Systems
Deep learning inference on embedded devices is a burgeoning field with m...
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DoubleEnsemble: A New Ensemble Method Based on Sample Reweighting and Feature Selection for Financial Data Analysis
Modern machine learning models (such as deep neural networks and boostin...
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Kalman Filtering Attention for User Behavior Modeling in CTR Prediction
Clickthrough rate (CTR) prediction is one of the fundamental tasks for ...
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Loosely Coupled Federated Learning Over Generative Models
Federated learning (FL) was proposed to achieve collaborative machine le...
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The Deep Learning Galerkin Method for the General Stokes Equations
The finite element method, finite difference method, finite volume metho...
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Decoupled Modified Characteristic Finite Element Method with Different Subdomain Time Steps for Nonstationary DualPorosityNavierStokes Model
In this paper, we develop the numerical theory of decoupled modified cha...
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LRSpeech: Extremely LowResource Speech Synthesis and Recognition
Speech synthesis (text to speech, TTS) and recognition (automatic speech...
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ACFD: Asymmetric Cartoon Face Detector
Cartoon face detection is a more challenging task than human face detect...
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Approximation Algorithms for Clustering with Dynamic Points
In many classic clustering problems, we seek to sketch a massive data se...
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Neural Architecture Optimization with Graph VAE
Due to their high computational efficiency on a continuous space, gradie...
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Improved Algorithms for ConvexConcave Minimax Optimization
This paper studies minimax optimization problems min_x max_y f(x,y), whe...
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Exploration by Maximizing Rényi Entropy for ZeroShot Meta RL
Exploring the transition dynamics is essential to the success of reinfor...
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ASFD: Automatic and Scalable Face Detector
In this paper, we propose a novel Automatic and Scalable Face Detector (...
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MetaEmbeddings Based On SelfAttention
Creating metaembeddings for better performance in language modelling ha...
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Convolutional Spectral Kernel Learning
Recently, nonstationary spectral kernels have drawn much attention, owi...
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PACache: Learningbased PopularityAware Content Caching in Edge Networks
With the aggressive growth of smart environments, a large amount of data...
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Online Algorithms for Multishop Ski Rental with Machine Learned Predictions
We study the problem of augmenting online algorithms with machine learne...
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Schema2QA: Answering Complex Queries on the Structured Web with a Neural Model
Virtual assistants today require every website to submit skills individu...
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Resource Sharing in the Edge: A Distributed BargainingTheoretic Approach
The growing demand for edge computing resources, particularly due to inc...
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Let's Share: A GameTheoretic Framework for Resource Sharing in Mobile Edge Clouds
Mobile edge computing seeks to provide resources to different delaysens...
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Neuron Interaction Based Representation Composition for Neural Machine Translation
Recent NLP studies reveal that substantial linguistic information can be...
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LearningAssisted Competitive Algorithms for PeakAware Energy Scheduling
In this paper, we study the peakaware energy scheduling problem using t...
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Fast Learning of Temporal Action Proposal via Dense Boundary Generator
Generating temporal action proposals remains a very challenging problem,...
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Algorithms and Adaptivity Gaps for Stochastic kTSP
Given a metric (V,d) and a root∈ V, the classic kTSP problem is to find...
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Metric Classification Network in Actual Face Recognition Scene
In order to make facial features more discriminative, some new models ha...
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Optimizing Speech Recognition For The Edge
While most deployed speech recognition systems today still run on server...
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Automated Spectral Kernel Learning
The generalization performance of kernel methods is largely determined b...
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Learning Vectorvalued Functions with Local Rademacher Complexity
We consider a general family of problems of which the output space admit...
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Learning Guided Convolutional Network for Depth Completion
Dense depth perception is critical for autonomous driving and other robo...
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NetSMF: LargeScale Network Embedding as Sparse Matrix Factorization
We study the problem of largescale network embedding, which aims to lea...
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Gradient Descent Maximizes the Margin of Homogeneous Neural Networks
Recent works on implicit regularization have shown that gradient descent...
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Distributed Learning with Random Features
Distributed learning and random projections are the most common techniqu...
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TSRNN: Text Steganalysis Based on Recurrent Neural Networks
With the rapid development of natural language processing technologies, ...
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Policy Search by Target Distribution Learning for Continuous Control
We observe that several existing policy gradient methods (such as vanill...
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Robust Variational Autoencoder
Machine learning methods often need a large amount of labeled training d...
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AntiConfusing: RegionAware Network for Human Pose Estimation
In this work, we propose a novel framework named RegionAware Network (R...
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Automatic Target Recognition Using Discrimination Based on Optimal Transport
The use of distances based on optimal transportation has recently shown ...
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Jian Li
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Assistant Professor at Institute for Interdisciplinary Information Sciences (IIIS, previously ITCS), Tsinghua University