b'Hai Li'

research

∙ 09/08/2023

Depth Completion with Multiple Balanced Bases and Confidence for Dense Monocular SLAM

Dense SLAM based on monocular cameras does indeed have immense applicati...

0 Weijian Xie, et al. ∙

research

∙ 08/16/2023

Stable and Causal Inference for Discriminative Self-supervised Deep Visual Representations

In recent years, discriminative self-supervised methods have made signif...

0 Yuewei Yang, et al. ∙

research

∙ 06/15/2023

OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection

Out-of-Distribution (OOD) detection is critical for the reliable operati...

0 Jingyang Zhang, et al. ∙

research

∙ 06/09/2023

FLSL: Feature-level Self-supervised Learning

Current self-supervised learning (SSL) methods (e.g., SimCLR, DINO, VICR...

0 Qing Su, et al. ∙

research

∙ 03/25/2023

SIO: Synthetic In-Distribution Data Benefits Out-of-Distribution Detection

Building up reliable Out-of-Distribution (OOD) detectors is challenging,...

0 Jingyang Zhang, et al. ∙

research

∙ 03/16/2023

3D Masked Autoencoding and Pseudo-labeling for Domain Adaptive Segmentation of Heterogeneous Infant Brain MRI

Robust segmentation of infant brain MRI across multiple ages, modalities...

0 Xuzhe Zhang, et al. ∙

research

∙ 02/08/2023

Disentangling Learning Representations with Density Estimation

Disentangled learning representations have promising utility in many app...

0 Eric Yeats, et al. ∙

research

∙ 01/31/2023

GDOD: Effective Gradient Descent using Orthogonal Decomposition for Multi-Task Learning

Multi-task learning (MTL) aims at solving multiple related tasks simulta...

0 Xin Dong, et al. ∙

research

∙ 01/18/2023

HCE: Improving Performance and Efficiency with Heterogeneously Compressed Neural Network Ensemble

Ensemble learning has gain attention in resent deep learning research as...

0 Jingchi Zhang, et al. ∙

research

∙ 12/08/2022

Adaptive Neural Network Backstepping Control Method for Aerial Manipulator Based on Variable Inertia Parameter Modeling

For the aerial manipulator that performs aerial work tasks, the actual o...

0 Hai Li, et al. ∙

research

∙ 11/28/2022

PIDS: Joint Point Interaction-Dimension Search for 3D Point Cloud

The interaction and dimension of points are two important axes in design...

0 Tunhou Zhang, et al. ∙

research

∙ 11/11/2022

More Generalized and Personalized Unsupervised Representation Learning In A Distributed System

Discriminative unsupervised learning methods such as contrastive learnin...

0 Yuewei Yang, et al. ∙

research

∙ 11/06/2022

Preserving background sound in noise-robust voice conversion via multi-task learning

Background sound is an informative form of art that is helpful in provid...

0 Jixun Yao, et al. ∙

research

∙ 10/02/2022

Approximate Computing and the Efficient Machine Learning Expedition

Approximate computing (AxC) has been long accepted as a design alternati...

0 Jörg Henkel, et al. ∙

research

∙ 09/30/2022

Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction

Due to limited communication capacities of edge devices, most existing f...

0 Jianyi Zhang, et al. ∙

research

∙ 09/21/2022

NashAE: Disentangling Representations through Adversarial Covariance Minimization

We present a self-supervised method to disentangle factors of variation ...

4 Eric Yeats, et al. ∙

research

∙ 09/09/2022

Fine-grain Inference on Out-of-Distribution Data with Hierarchical Classification

Machine learning methods must be trusted to make appropriate decisions i...

0 Randolph Linderman, et al. ∙

research

∙ 09/08/2022

FADE: Enabling Large-Scale Federated Adversarial Training on Resource-Constrained Edge Devices

Adversarial Training (AT) has been proven to be an effective method of i...

0 Minxue Tang, et al. ∙

research

∙ 09/08/2022

Joint Optimization of STAR-RIS Assisted UAV Communication Systems

In this letter, we study the simultaneously transmitting and reflecting ...

0 Qin Zhang, et al. ∙

research

∙ 08/26/2022

Learning and Compositionality: a Unification Attempt via Connectionist Probabilistic Programming

We consider learning and compositionality as the key mechanisms towards ...

0 Ximing Qiao, et al. ∙

research

∙ 08/23/2022

Self-Trained Proposal Networks for the Open World

Deep learning-based object proposal methods have enabled significant adv...

0 Matthew Inkawhich, et al. ∙

research

∙ 08/21/2022

Vox-Surf: Voxel-based Implicit Surface Representation

Virtual content creation and interaction play an important role in moder...

0 Hai Li, et al. ∙

research

∙ 07/14/2022

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems

The rise of deep neural networks provides an important driver in optimiz...

0 Tunhou Zhang, et al. ∙

research

∙ 02/21/2022

Privacy Leakage of Adversarial Training Models in Federated Learning Systems

Adversarial Training (AT) is crucial for obtaining deep neural networks ...

0 Jingyang Zhang, et al. ∙

research

∙ 11/17/2021

ReaLPrune: ReRAM Crossbar-aware Lottery Ticket Pruned CNNs

Training machine learning (ML) models at the edge (on-chip training on e...

0 Biresh Kumar Joardar, et al. ∙

research

∙ 10/26/2021

FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective

Federated learning (FL) is a popular distributed learning framework that...

0 Jingwei Sun, et al. ∙

research

∙ 10/23/2021

A Layer-wise Adversarial-aware Quantization Optimization for Improving Robustness

Neural networks are getting better accuracy with higher energy and compu...

0 Chang Song, et al. ∙

research

∙ 10/10/2021

NViT: Vision Transformer Compression and Parameter Redistribution

Transformers yield state-of-the-art results across many tasks. However, ...

0 Huanrui Yang, et al. ∙

research

∙ 07/03/2021

Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective

Learning with graphs has attracted significant attention recently. Exist...

0 Binghui Wang, et al. ∙

research

∙ 06/07/2021

Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure

Enabling out-of-distribution (OOD) detection for DNNs is critical for th...

0 Jingyang Zhang, et al. ∙

research

∙ 04/21/2021

Neuromorphic Algorithm-hardware Codesign for Temporal Pattern Learning

Neuromorphic computing and spiking neural networks (SNN) mimic the behav...

14 Haowen Fang, et al. ∙

research

∙ 03/17/2021

Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap?

We design blackbox transfer-based targeted adversarial attacks for an en...

0 Nathan Inkawhich, et al. ∙

research

∙ 03/17/2021

The Untapped Potential of Off-the-Shelf Convolutional Neural Networks

Over recent years, a myriad of novel convolutional network architectures...

13 Matthew Inkawhich, et al. ∙

research

∙ 03/02/2021

A Case for 3D Integrated System Design for Neuromorphic Computing AI Applications

Over the last decade, artificial intelligence has found many application...

0 Eren Kurshan, et al. ∙

research

∙ 02/20/2021

BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization

Mixed-precision quantization can potentially achieve the optimal tradeof...

0 Huanrui Yang, et al. ∙

research

∙ 01/19/2021

On Provable Backdoor Defense in Collaborative Learning

As collaborative learning allows joint training of a model using multipl...

0 Ximing Qiao, et al. ∙

research

∙ 12/29/2020

Improving Adversarial Robustness in Weight-quantized Neural Networks

Neural networks are getting deeper and more computation-intensive nowada...

0 Chang Song, et al. ∙

research

∙ 12/08/2020

Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective

Federated learning (FL) is a popular distributed learning framework that...

0 Jingwei Sun, et al. ∙

research

∙ 12/08/2020

GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs

Graph-based semi-supervised node classification (GraphSSC) has wide appl...

0 Binghui Wang, et al. ∙

research

∙ 11/30/2020

ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition

Scale variance among different sizes of body parts and objects is a chal...

0 Hsin-Pai Cheng, et al. ∙

research

∙ 11/26/2020

Fast IR Drop Estimation with Machine Learning

IR drop constraint is a fundamental requirement enforced in almost all c...

0 Zhiyao Xie, et al. ∙

research

∙ 11/06/2020

Low-Cost Floating-Point Processing in ReRAM for Scientific Computing

We propose ReFloat, a principled approach for low-cost floating-point pr...

0 Linghao Song, et al. ∙

research

∙ 10/29/2020

The IQIYI System for Voice Conversion Challenge 2020

This paper presents the IQIYI voice conversion system (T24) for Voice Co...

0 Wendong Gan, et al. ∙

research

∙ 09/30/2020

DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles

Recent research finds CNN models for image classification demonstrate ov...

11 Huanrui Yang, et al. ∙

research

∙ 09/01/2020

Evasion Attacks to Graph Neural Networks via Influence Function

Graph neural networks (GNNs) have achieved state-of-the-art performance ...

0 Binghui Wang, et al. ∙

research

∙ 09/01/2020

Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs

Link prediction in dynamic graphs (LPDG) is an important research proble...

4 Houxiang Fan, et al. ∙

research

∙ 08/07/2020

LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets

Federated learning is a popular distributed machine learning paradigm wi...

12 Ang Li, et al. ∙

research

∙ 07/08/2020

NASGEM: Neural Architecture Search via Graph Embedding Method

Neural Architecture Search (NAS) automates and prospers the design of ne...

0 Hsin-Pai Cheng, et al. ∙

research

∙ 06/12/2020

Defending against GAN-based Deepfake Attacks via Transformation-aware Adversarial Faces

Deepfake represents a category of face-swapping attacks that leverage ma...

0 Chaofei Yang, et al. ∙

research

∙ 05/14/2020

PENNI: Pruned Kernel Sharing for Efficient CNN Inference

Although state-of-the-art (SOTA) CNNs achieve outstanding performance on...

0 Shiyu Li, et al. ∙

Hai Li

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