b'Yi Sun'

research

∙ 08/29/2023

Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints

Unlike cloud-based deep learning models that are often large and uniform...

0 Wenxing Xu, et al. ∙

research

∙ 08/17/2023

Accelerating Aggregation Queries on Unstructured Streams of Data

Analysts and scientists are interested in querying streams of video, aud...

0 Matthew Russo, et al. ∙

research

∙ 08/09/2023

Learning multi-domain feature relation for visible and Long-wave Infrared image patch matching

Recently, learning-based algorithms have achieved promising performance ...

0 Xiuwei Zhang, et al. ∙

research

∙ 06/19/2023

AdaSelection: Accelerating Deep Learning Training through Data Subsampling

In this paper, we introduce AdaSelection, an adaptive sub-sampling metho...

0 Minghe Zhang, et al. ∙

research

∙ 05/31/2023

Learning Task-preferred Inference Routes for Gradient De-conflict in Multi-output DNNs

Multi-output deep neural networks(MONs) contain multiple task branches, ...

0 Yi Sun, et al. ∙

research

∙ 03/28/2023

Boundary-to-Solution Mapping for Groundwater Flows in a Toth Basin

In this paper, the authors propose a new approach to solving the groundw...

0 Jingwei Sun, et al. ∙

research

∙ 12/13/2022

FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data

Today, recommender systems have played an increasingly important role in...

0 Minghong Fang, et al. ∙

research

∙ 12/07/2022

Artificial Intelligence Security Competition (AISC)

The security of artificial intelligence (AI) is an important research ar...

12 Yinpeng Dong, et al. ∙

research

∙ 11/09/2022

ZK-IMG: Attested Images via Zero-Knowledge Proofs to Fight Disinformation

Over the past few years, AI methods of generating images have been incre...

0 Daniel Kang, et al. ∙

research

∙ 10/17/2022

Scaling up Trustless DNN Inference with Zero-Knowledge Proofs

As ML models have increased in capabilities and accuracy, so has the com...

0 Daniel Kang, et al. ∙

research

∙ 07/16/2022

TransGrasp: Grasp Pose Estimation of a Category of Objects by Transferring Grasps from Only One Labeled Instance

Grasp pose estimation is an important issue for robots to interact with ...

0 Hongtao Wen, et al. ∙

research

∙ 06/17/2022

Accelerated Kinetic Monte Carlo methods for general nonlocal traffic flow models

This paper presents a class of one-dimensional cellular automata (CA) mo...

0 Yi Sun, et al. ∙

research

∙ 05/12/2022

Using Natural Sentences for Understanding Biases in Language Models

Evaluation of biases in language models is often limited to syntheticall...

0 Sarah Alnegheimish, et al. ∙

research

∙ 09/08/2021

NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task–Next Sentence Prediction

Using prompts to utilize language models to perform various downstream t...

0 Yi Sun, et al. ∙

research

∙ 07/02/2021

Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM

Motivated by applications to single-particle cryo-electron microscopy (c...

0 Zhou Fan, et al. ∙

research

∙ 06/18/2021

ICINet: ICI-Aware Neural Network Based Channel Estimation for Rapidly Time-Varying OFDM Systems

A novel intercarrier interference (ICI)-aware orthogonal frequency divis...

0 Yi Sun, et al. ∙

research

∙ 03/25/2021

Preserve, Promote, or Attack? GNN Explanation via Topology Perturbation

Prior works on formalizing explanations of a graph neural network (GNN) ...

10 Yi Sun, et al. ∙

research

∙ 10/21/2020

Data augmentation as stochastic optimization

We present a theoretical framework recasting data augmentation as stocha...

0 Boris Hanin, et al. ∙

research

∙ 06/25/2020

Multi-Agent Deep Reinforcement Learning for HVAC Control in Commercial Buildings

In commercial buildings, about 40 is attributed to Heating, Ventilation,...

0 Liang Yu, et al. ∙

research

∙ 03/31/2020

Likelihood landscape and maximum likelihood estimation for the discrete orbit recovery model

We study the non-convex optimization landscape for maximum likelihood es...

0 Zhou Fan, et al. ∙

research

∙ 02/13/2020

Multi-objective Ranking via Constrained Optimization

In this paper, we introduce an Augmented Lagrangian based method to inco...

0 Michinari Momma, et al. ∙

research

∙ 09/14/2019

Line as object: datasets and framework for semantic line segment detection

In this work, we propose a learning-based approach to the task of detect...

10 Yi Sun, et al. ∙

research

∙ 08/21/2019

Testing Robustness Against Unforeseen Adversaries

Considerable work on adversarial defense has studied robustness to a fix...

1 Daniel Kang, et al. ∙

research

∙ 08/19/2019

Learning Fair Classifiers in Online Stochastic Settings

In many real life situations, including job and loan applications, gatek...

0 Yi Sun, et al. ∙

research

∙ 06/15/2019

Txilm: Lossy Block Compression with Salted Short Hashing

Current blockchains are restricted by the low throughput. Aimed at this ...

0 Donghui Ding, et al. ∙

research

∙ 05/03/2019

Transfer of Adversarial Robustness Between Perturbation Types

We study the transfer of adversarial robustness of deep neural networks ...

12 Daniel Kang, et al. ∙

research

∙ 03/22/2019

Principal components in linear mixed models with general bulk

We study the outlier eigenvalues and eigenvectors in variance components...

0 Zhou Fan, et al. ∙

research

∙ 12/12/2018

An Active-Passive Measurement Study of TCP Performance over LTE on High-speed Rails

High-speed rail (HSR) systems potentially provide a more efficient way o...

0 Jing Wang, et al. ∙

research

∙ 12/04/2018

Learning Vine Copula Models For Synthetic Data Generation

A vine copula model is a flexible high-dimensional dependence model whic...

6 Yi Sun, et al. ∙

research

∙ 11/20/2018

Limited Gradient Descent: Learning With Noisy Labels

Label noise may handicap the generalization of classifiers, and it is an...

14 Yi Sun, et al. ∙

research

∙ 06/25/2018

Spiked covariances and principal components analysis in high-dimensional random effects models

We study principal components analyses in multivariate random and mixed ...

0 Zhou Fan, et al. ∙

research

∙ 03/09/2017

Development of a computer-aided design software for dental splint in orthognathic surgery

In the orthognathic surgery, dental splints are important and necessary ...

0 Xiaojun Chen, et al. ∙

research

∙ 12/07/2015

Sparsifying Neural Network Connections for Face Recognition

This paper proposes to learn high-performance deep ConvNets with sparse ...

0 Yi Sun, et al. ∙

research

∙ 11/02/2015

From random walks to distances on unweighted graphs

Large unweighted directed graphs are commonly used to capture relations ...

0 Tatsunori B. Hashimoto, et al. ∙

research

∙ 02/03/2015

DeepID3: Face Recognition with Very Deep Neural Networks

The state-of-the-art of face recognition has been significantly advanced...

0 Yi Sun, et al. ∙

research

∙ 12/03/2014

Deeply learned face representations are sparse, selective, and robust

This paper designs a high-performance deep convolutional network (DeepID...

0 Yi Sun, et al. ∙

research

∙ 11/20/2014

Metric recovery from directed unweighted graphs

We analyze directed, unweighted graphs obtained from x_i∈R^d by connecti...

0 Tatsunori B. Hashimoto, et al. ∙

research

∙ 06/18/2014

Deep Learning Face Representation by Joint Identification-Verification

The key challenge of face recognition is to develop effective feature re...

0 Yi Sun, et al. ∙

research

∙ 09/26/2012

Efficient Natural Evolution Strategies

Efficient Natural Evolution Strategies (eNES) is a novel alternative to ...

0 Yi Sun, et al. ∙

research

∙ 06/18/2012

On the Size of the Online Kernel Sparsification Dictionary

We analyze the size of the dictionary constructed from online kernel spa...

0 Yi Sun, et al. ∙

research

∙ 06/22/2011

Natural Evolution Strategies

This paper presents Natural Evolution Strategies (NES), a recent family ...

0 Daan Wierstra, et al. ∙

research

∙ 06/10/2011

A Linear Time Natural Evolution Strategy for Non-Separable Functions

We present a novel Natural Evolution Strategy (NES) variant, the Rank-On...

0 Yi Sun, et al. ∙

research

∙ 03/29/2011

Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments

To maximize its success, an AGI typically needs to explore its initially...

0 Yi Sun, et al. ∙

Yi Sun

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