b'Ce Zhang'

research

∙ 05/11/2023

SalienDet: A Saliency-based Feature Enhancement Algorithm for Object Detection for Autonomous Driving

Object detection (OD) is crucial to autonomous driving. Unknown objects ...

0 Ning Ding, et al. ∙

research

∙ 04/15/2023

Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical Systems

Given an unknown dynamical system, what is the minimum number of samples...

0 Ce Zhang, et al. ∙

research

∙ 03/20/2023

Self-Correctable and Adaptable Inference for Generalizable Human Pose Estimation

A central challenge in human pose estimation, as well as in many other m...

0 Zhehan Kan, et al. ∙

research

∙ 03/13/2023

High-throughput Generative Inference of Large Language Models with a Single GPU

The high computational and memory requirements of large language model (...

0 Ying Sheng, et al. ∙

research

∙ 03/02/2023

Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptation

Fully test-time adaptation aims to adapt the network model based on sequ...

0 Yushun Tang, et al. ∙

research

∙ 02/01/2023

Hierarchical Classification of Research Fields in the "Web of Science" Using Deep Learning

The scholarly publication space is growing steadily not just in numbers ...

0 Susie Xi Rao, et al. ∙

research

∙ 12/16/2022

Convolution-enhanced Evolving Attention Networks

Attention-based neural networks, such as Transformers, have become ubiqu...

0 Yujing Wang, et al. ∙

research

∙ 11/16/2022

Holistic Evaluation of Language Models

Language models (LMs) are becoming the foundation for almost all major l...

21 Percy Liang, et al. ∙

research

∙ 11/07/2022

EEG-Fest: Few-shot based Attention Network for Driver's Vigilance Estimation with EEG Signals

A lack of driver's vigilance is the main cause of most vehicle crashes. ...

0 Ning Ding, et al. ∙

research

∙ 10/18/2022

Number-Adaptive Prototype Learning for 3D Point Cloud Semantic Segmentation

3D point cloud semantic segmentation is one of the fundamental tasks for...

0 Yangheng Zhao, et al. ∙

research

∙ 09/28/2022

Neural Methods for Logical Reasoning Over Knowledge Graphs

Reasoning is a fundamental problem for computers and deeply studied in A...

0 Alfonso Amayuelas, et al. ∙

research

∙ 09/12/2022

CARE: Certifiably Robust Learning with Reasoning via Variational Inference

Despite great recent advances achieved by deep neural networks (DNNs), t...

2 Jiawei Zhang, et al. ∙

research

∙ 08/17/2022

New primitives for bounded degradation in network service

Certain new ascendant data center workloads can absorb some degradation ...

0 Simon Kassing, et al. ∙

research

∙ 07/20/2022

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM

Federated learning (FL) enables distributed devices to jointly train a s...

4 Chulin Xie, et al. ∙

research

∙ 07/20/2022

DataPerf: Benchmarks for Data-Centric AI Development

Machine learning (ML) research has generally focused on models, while th...

17 Mark Mazumder, et al. ∙

research

∙ 07/05/2022

Keyword Extraction in Scientific Documents

The scientific publication output grows exponentially. Therefore, it is ...

0 Susie Xi Rao, et al. ∙

research

∙ 06/20/2022

GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks

As one of the most popular machine learning models today, graph neural n...

0 Kenza Amara, et al. ∙

research

∙ 06/13/2022

Contrastive Learning for Unsupervised Domain Adaptation of Time Series

Unsupervised domain adaptation (UDA) aims at learning a machine learning...

0 Yilmazcan Özyurt, et al. ∙

research

∙ 06/12/2022

Stochastic Gradient Descent without Full Data Shuffle

Stochastic gradient descent (SGD) is the cornerstone of modern machine l...

39 Lijie Xu, et al. ∙

research

∙ 06/08/2022

FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization

Hyperparameter optimization (HPO) is crucial for machine learning algori...

0 Zhen Wang, et al. ∙

research

∙ 06/02/2022

Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees

Communication compression is a crucial technique for modern distributed ...

1 Jue Wang, et al. ∙

research

∙ 06/02/2022

Decentralized Training of Foundation Models in Heterogeneous Environments

Training foundation models, such as GPT-3 and PaLM, can be extremely exp...

8 Binhang Yuan, et al. ∙

research

∙ 05/25/2022

BRIGHT – Graph Neural Networks in Real-Time Fraud Detection

Detecting fraudulent transactions is an essential component to control r...

0 Mingxuan Lu, et al. ∙

research

∙ 04/22/2022

Modelling graph dynamics in fraud detection with "Attention"

At online retail platforms, detecting fraudulent accounts and transactio...

0 Susie Xi Rao, et al. ∙

research

∙ 04/06/2022

X-CAR: An Experimental Vehicle Platform for Connected Autonomy Research Powered by CARMA

Autonomous vehicles promise a future with a safer, cleaner, more efficie...

0 Goodarz Mehr, et al. ∙

research

∙ 04/04/2022

SHiFT: An Efficient, Flexible Search Engine for Transfer Learning

Transfer learning can be seen as a data- and compute-efficient alternati...

21 Cedric Renggli, et al. ∙

research

∙ 03/04/2022

A Quality Index Metric and Method for Online Self-Assessment of Autonomous Vehicles Sensory Perception

Perception is critical to autonomous driving safety. Camera-based object...

8 Ce Zhang, et al. ∙

research

∙ 02/24/2022

Experiments as Code: A Concept for Reproducible, Auditable, Debuggable, Reusable, Scalable Experiments

A common concern in experimental research is the auditability and reprod...

0 Leonel Aguilar, et al. ∙

research

∙ 02/03/2022

Certifying Out-of-Domain Generalization for Blackbox Functions

Certifying the robustness of model performance under bounded data distri...

7 Maurice Weber, et al. ∙

research

∙ 01/05/2022

TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets

Tables have been an ever-existing structure to store data. There exist n...

0 Susie Xi Rao, et al. ∙

research

∙ 12/17/2021

Super-resolution reconstruction of cytoskeleton image based on A-net deep learning network

To date, live-cell imaging at the nanometer scale remains challenging. E...

7 Qian Chen, et al. ∙

research

∙ 12/15/2021

Dynamic Human Evaluation for Relative Model Comparisons

Collecting human judgements is currently the most reliable evaluation me...

0 Þórhildur Þorleiksdóttir, et al. ∙

research

∙ 09/19/2021

Towards Automatic Bias Detection in Knowledge Graphs

With the recent surge in social applications relying on knowledge graphs...

0 Daphna Keidar, et al. ∙

research

∙ 09/18/2021

Efficient Hybrid Transformer: Learning Global-local Context for Urban Sence Segmentation

Semantic segmentation of fine-resolution urban scene images plays a vita...

0 Libo Wang, et al. ∙

research

∙ 08/30/2021

Evaluating Bayes Error Estimators on Read-World Datasets with FeeBee

The Bayes error rate (BER) is a fundamental concept in machine learning ...

0 Cedric Renggli, et al. ∙

research

∙ 08/14/2021

LinkTeller: Recovering Private Edges from Graph Neural Networks via Influence Analysis

Graph structured data have enabled several successful applications such ...

0 Fan Wu, et al. ∙

research

∙ 06/21/2021

Attention-based Neural Network for Driving Environment Complexity Perception

Environment perception is crucial for autonomous vehicle (AV) safety. Mo...

0 Ce Zhang, et al. ∙

research

∙ 06/11/2021

Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks

Despite the great successes achieved by deep neural networks (DNNs), rec...

0 Nezihe Merve Gürel, et al. ∙

research

∙ 05/17/2021

Towards Demystifying Serverless Machine Learning Training

The appeal of serverless (FaaS) has triggered a growing interest on how ...

17 Jiawei Jiang, et al. ∙

research

∙ 04/12/2021

Multilingual Language Models Predict Human Reading Behavior

We analyze if large language models are able to predict patterns of huma...

0 Nora Hollenstein, et al. ∙

research

∙ 04/12/2021

Distributed Learning Systems with First-order Methods

Scalable and efficient distributed learning is one of the main driving f...

0 Ji Liu, et al. ∙

research

∙ 04/01/2021

TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness

Adversarial Transferability is an intriguing property of adversarial exa...

0 Zhuolin Yang, et al. ∙

research

∙ 03/20/2021

DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation

Recent success of deep neural networks (DNNs) hinges on the availability...

0 Boxin Wang, et al. ∙

research

∙ 03/13/2021

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting

Multivariate time-series forecasting plays a crucial role in many real-w...

0 Defu Cao, et al. ∙

research

∙ 02/17/2021

Switch Spaces: Learning Product Spaces with Sparse Gating

Learning embedding spaces of suitable geometry is critical for represent...

6 Shuai Zhang, et al. ∙

research

∙ 02/17/2021

Decoding EEG Brain Activity for Multi-Modal Natural Language Processing

Until recently, human behavioral data from reading has mainly been of in...

0 Nora Hollenstein, et al. ∙

research

∙ 02/15/2021

A Data Quality-Driven View of MLOps

Developing machine learning models can be seen as a process similar to t...

0 Cedric Renggli, et al. ∙

research

∙ 02/04/2021

1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed

Scalable training of large models (like BERT and GPT-3) requires careful...

0 Hanlin Tang, et al. ∙

research

∙ 01/24/2021

EEG-Inception: An Accurate and Robust End-to-End Neural Network for EEG-based Motor Imagery Classification

Classification of EEG-based motor imagery (MI) is a crucial non-invasive...

21 Ce Zhang, et al. ∙

research

∙ 12/20/2020

Suspicious Massive Registration Detection via Dynamic Heterogeneous Graph Neural Networks

Massive account registration has raised concerns on risk management in e...

0 Susie Xi Rao, et al. ∙

Ce Zhang

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