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09/11/2023
Low-Complexity Vector Source Coding for Discrete Long Sequences with Unknown Distributions
In this paper, we propose a source coding scheme that represents data fr...
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08/02/2023
Tango: rethinking quantization for graph neural network training on GPUs
Graph Neural Networks (GNNs) are becoming increasingly popular due to th...
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06/19/2023
Differentially Private Over-the-Air Federated Learning Over MIMO Fading Channels
Federated learning (FL) enables edge devices to collaboratively train ma...
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03/27/2023
Nonparametric approaches for analyzing carbon emission: from statistical and machine learning perspectives
Linear regression models, especially the extended STIRPAT model, are rou...
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03/20/2023
Some novel aspects of quantile regression: local stationarity, random forests and optimal transportation
This paper is written for a Festschrift in honour of Professor Marc Hall...
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01/16/2023
Theoretical and computational aspects of robust optimal transportation, with applications to statistics and machine learning
Optimal transport (OT) theory and the related p-Wasserstein distance (W_...
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12/20/2022
Nonparametric Measure-Transportation-Based Methods for Directional Data
This paper proposes various nonparametric tools based on measure transpo...
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11/16/2022
Two-Sample Test for Stochastic Block Models via the Largest Singular Value
The stochastic block model is widely used for detecting community struct...
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09/09/2022
Quantiles, Ranks and Signs in Metric Spaces
Non-Euclidean data is currently prevalent in many fields, necessitating ...
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08/25/2022
Center-outward Rank- and Sign-based VARMA Portmanteau Tests
Revisiting the pseudo-Gaussian tests of Chitturi (1974), Hosking (1980),...
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08/09/2022
Motif-based Graph Representation Learning with Application to Chemical Molecules
This work considers the task of representation learning on the attribute...
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08/07/2022
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining
Transformers are considered one of the most important deep learning mode...
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07/26/2022
CFLIT: Coexisting Federated Learning and Information Transfer
Future wireless networks are expected to support diverse mobile services...
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10/15/2021
Detecting Gender Bias in Transformer-based Models: A Case Study on BERT
In this paper, we propose a novel gender bias detection method by utiliz...
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10/15/2021
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm
Various pruning approaches have been proposed to reduce the footprint re...
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09/16/2021
Dr. Top-k: Delegate-Centric Top-k on GPUs
Recent top-k computation efforts explore the possibility of revising var...
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09/13/2021
Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search
Molecular similarity search has been widely used in drug discovery to id...
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09/06/2021
Reconfigurable Intelligent Surface Empowered Over-the-Air Federated Edge Learning
Federated edge learning (FEEL) has emerged as a revolutionary paradigm t...
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08/10/2021
Binary Complex Neural Network Acceleration on FPGA
Being able to learn from complex data with phase information is imperati...
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07/27/2021
Angel's Girl for Blind Painters: an Efficient Painting Navigation System Validated by Multimodal Evaluation Approach
For people who ardently love painting but unfortunately have visual impa...
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07/20/2021
Relay-Assisted Cooperative Federated Learning
Federated learning (FL) has recently emerged as a promising technology t...
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07/06/2021
PM-LSH: a fast and accurate in-memory framework for high-dimensional approximate NN and closest pair search
Nearest neighbor (NN) search is inherently computationally expensive in ...
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06/16/2021
FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator
Recent works demonstrated the promise of using resistive random access m...
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05/12/2021
SimNet: Computer Architecture Simulation using Machine Learning
While cycle-accurate simulators are essential tools for architecture res...
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03/14/2021
TRUST: Triangle Counting Reloaded on GPUs
Triangle counting is a building block for a wide range of graph applicat...
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03/11/2021
TAG: Transformer Attack from Gradient
Although federated learning has increasingly gained attention in terms o...
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02/22/2021
CSIT-Free Federated Edge Learning via Reconfigurable Intelligent Surface
We study over-the-air model aggregation in federated edge learning (FEEL...
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02/09/2021
Conversational Query Rewriting with Self-supervised Learning
Context modeling plays a critical role in building multi-turn dialogue s...
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01/18/2021
Semi-Blind Cascaded Channel Estimation for Reconfigurable Intelligent Surface Aided Massive MIMO
Reconfigurable intelligent surface (RIS) is envisioned to be a promising...
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11/20/2020
Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach
To exploit massive amounts of data generated at mobile edge networks, fe...
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11/11/2020
Rank-Based Testing for Semiparametric VAR Models: a measure transportation approach
We develop a class of tests for semiparametric vector autoregressive (VA...
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09/18/2020
C-SAW: A Framework for Graph Sampling and Random Walk on GPUs
Many applications require to learn, mine, analyze and visualize large-sc...
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09/17/2020
Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning
Pretrained large-scale language models have increasingly demonstrated hi...
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09/14/2020
SAPAG: A Self-Adaptive Privacy Attack From Gradients
Distributed learning such as federated learning or collaborative learnin...
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08/28/2020
MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks
Deep learning or deep neural networks (DNNs) have nowadays enabled high ...
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07/17/2020
EZLDA: Efficient and Scalable LDA on GPUs
LDA is a statistical approach for topic modeling with a wide range of ap...
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07/16/2020
FTRANS: Energy-Efficient Acceleration of Transformers using FPGA
In natural language processing (NLP), the "Transformer" architecture was...
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07/02/2020
GSoFa: Scalable Sparse LU Symbolic Factorization on GPUs
Decomposing a matrix A into a lower matrix L and an upper matrix U, whic...
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03/06/2020
Statistical Beamforming for FDD Downlink Massive MIMO via Spatial Information Extraction and Beam Selection
In this paper, we study the beamforming design problem in frequency-divi...
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01/29/2020
M-estimation in GARCH models without higher order moments
We consider a class of M-estimators of the parameters of the GARCH model...
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01/02/2020
Reconfigurable-Intelligent-Surface Empowered 6G Wireless Communications: Challenges and Opportunities
Although the commercialization of fifth-generation (5G) mobile networks ...
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12/19/2019
Matrix-Calibration-Based Cascaded Channel Estimation for Reconfigurable Intelligent Surface Assisted Multiuser MIMO
Reconfigurable intelligent surface (RIS) is envisioned to be an essentia...
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12/13/2019
R-estimators in GARCH models; asymptotics, applications and bootstrapping
The quasi-maximum likelihood estimation is a commonly-used method for es...
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10/25/2019
Double-Sparsity Learning Based Channel-and-Signal Estimation in Massive MIMO with Generalized Spatial Modulation
In this paper, we study joint antenna activity detection, channel estima...
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10/18/2019
Center-Outward R-Estimation for Semiparametric VARMA Models
We propose a new class of estimators for semiparametric VARMA models wit...
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12/10/2018
SIMD-X: Programming and Processing of Graph Algorithms on GPUs
With high computation power and memory bandwidth, graphics processing un...
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11/21/2018
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks
The performance and efficiency of distributed training of Deep Neural Ne...
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10/02/2018
Super-Resolution Blind Channel-and-Signal Estimation for Massive MIMO with Arbitrary Array Geometry
In this paper, we study blind channel-and-signal estimation by exploitin...
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07/17/2018
Multi-Tenant Cross-Slice Resource Orchestration: A Deep Reinforcement Learning Approach
In a software-defined radio access network (RAN), a major challenge lies...
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07/17/2018