
Populationcoding and Dynamicneurons improved Spiking Actor Network for Reinforcement Learning
With the Deep Neural Networks (DNNs) as a powerful function approximator...
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AutoFuzzyJoin: AutoProgram Fuzzy Similarity Joins Without Labeled Examples
Fuzzy similarity join is an important database operator widely used in p...
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Optimal dimension dependence of the MetropolisAdjusted Langevin Algorithm
Conventional wisdom in the sampling literature, backed by a popular diff...
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KHOVID: Interoperable Privacy Preserving Digital Contact Tracing
During a pandemic, contact tracing is an essential tool to drive down th...
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An EndtoEnd Solution for Named Entity Recognition in eCommerce Search
Named entity recognition (NER) is a critical step in modern search query...
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Distilling a Deep Neural Network into a TakagiSugenoKang Fuzzy Inference System
Deep neural networks (DNNs) demonstrate great success in classification ...
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Tuning Convolutional Spiking Neural Network with Biologicallyplausible Reward Propagation
Spiking Neural Networks (SNNs) contain more biologyrealistic structures...
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Finite MetaDynamic Neurons in Spiking Neural Networks for Spatiotemporal Learning
Spiking Neural Networks (SNNs) have incorporated more biologicallyplaus...
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Answering MultiDimensional Range Queries under Local Differential Privacy
In this paper, we tackle the problem of answering multidimensional rang...
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Cooperative Reasoning on Knowledge Graph and Corpus: A MultiagentReinforcement Learning Approach
Knowledgegraphbased reasoning has drawn a lot of attention due to its ...
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Learning to Order Subquestions for Complex Question Answering
Answering complex questions involving multiple entities and relations is...
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Quantitative W_1 Convergence of LangevinLike Stochastic Processes with NonConvex Potential StateDependent Noise
We prove quantitative convergence rates at which discrete Langevinlike ...
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Is There an Analog of Nesterov Acceleration for MCMC?
We formulate gradientbased Markov chain Monte Carlo (MCMC) sampling as ...
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Quantitative Central Limit Theorems for Discrete Stochastic Processes
In this paper, we establish a generalization of the classical Central Li...
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Sharp Convergence Rates for Langevin Dynamics in the Nonconvex Setting
We study the problem of sampling from a distribution where the negative ...
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Index Modulation for 5G: Striving to Do More with Less
The fifth generation (5G) wireless communications brag both high spectru...
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Underdamped Langevin MCMC: A nonasymptotic analysis
We study the underdamped Langevin diffusion when the log of the target d...
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Convergence of Langevin MCMC in KLdivergence
Langevin diffusion is a commonly used tool for sampling from a given dis...
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FLAG n' FLARE: Fast LinearlyCoupled Adaptive Gradient Methods
We consider first order gradient methods for effectively optimizing a co...
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Asymptotic behavior of ℓ_pbased Laplacian regularization in semisupervised learning
Given a weighted graph with N vertices, consider a realvalued regressio...
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Xiang Cheng
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