b'Xuan Zhang'

research

∙ 06/15/2022

Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systems

Deep learning methods have been shown to be effective in representing gr...

Cong Fu, et al. ∙

research

∙ 05/18/2022

Demonstration of fully integrated parity-time-symmetric electronics

Harnessing parity-time (PT) symmetry with balanced gain and loss profile...

Weidong Cao, et al. ∙

research

∙ 04/27/2022

Domain Knowledge-Infused Deep Learning for Automated Analog/Radio-Frequency Circuit Parameter Optimization

The design automation of analog circuits is a longstanding challenge. Th...

Weidong Cao, et al. ∙

research

∙ 04/07/2022

Music Influence Modeling Based on Directed Network Model

Studying the history of music may provide a glimpse into the development...

Xuan Zhang, et al. ∙

research

∙ 04/05/2022

PDNPulse: Sensing PCB Anomaly with the Intrinsic Power Delivery Network

The ubiquitous presence of printed circuit boards (PCBs) in modern elect...

Huifeng Zhu, et al. ∙

research

∙ 03/14/2022

Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation

Personalized recommendation is an important class of deep-learning appli...

Liu Ke, et al. ∙

research

∙ 03/01/2022

Discovering Opportunities in New York City's Discovery Program: an Analysis of Affirmative Action Mechanisms

Discovery program (DISC) is an affirmative action policy used by the New...

Yuri Faenza, et al. ∙

research

∙ 02/26/2022

Domain Knowledge-Based Automated Analog Circuit Design with Deep Reinforcement Learning

The design automation of analog circuits is a longstanding challenge in ...

Weidong Cao, et al. ∙

research

∙ 02/10/2022

Robust and fair work allocation

In today's digital world, interaction with online platforms is ubiquitou...

Amine Allouah, et al. ∙

research

∙ 01/30/2022

Neural-PIM: Efficient Processing-In-Memory with Neural Approximation of Peripherals

Processing-in-memory (PIM) architectures have demonstrated great potenti...

Weidong Cao, et al. ∙

research

∙ 01/08/2022

A Fair and Efficient Hybrid Federated Learning Framework based on XGBoost for Distributed Power Prediction

In a modern power system, real-time data on power generation/consumption...

Haizhou Liu, et al. ∙

research

∙ 11/16/2021

Fairness-aware Online Price Discrimination with Nonparametric Demand Models

Price discrimination, which refers to the strategy of setting different ...

Xi Chen, et al. ∙

research

∙ 10/28/2021

A Sequence to Sequence Model for Extracting Multiple Product Name Entities from Dialog

E-commerce voice ordering systems need to recognize multiple product nam...

Praneeth Gubbala, et al. ∙

research

∙ 09/17/2021

On the Convergence of Tsetlin Machines for the AND and the OR Operators

The Tsetlin Machine (TM) is a novel machine-learning algorithm based on ...

Lei Jiao, et al. ∙

research

∙ 07/19/2021

LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation

Medical image segmentation plays an essential role in developing compute...

Guoping Xu, et al. ∙

research

∙ 03/22/2021

A Federated Learning Framework in Smart Grid: Securing Power Traces in Collaborative Learning

With the deployment of smart sensors and advancements in communication t...

Haizhou Liu, et al. ∙

research

∙ 03/15/2021

Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence

We study text representation methods using deep models. Current methods,...

Hongyang Gao, et al. ∙

research

∙ 01/25/2021

RTGPU: Real-Time GPU Scheduling of Hard Deadline Parallel Tasks with Fine-Grain Utilization

Many emerging cyber-physical systems, such as autonomous vehicles and ro...

An Zou, et al. ∙

research

∙ 01/19/2021

Disentangled Recurrent Wasserstein Autoencoder

Learning disentangled representations leads to interpretable models and ...

Jun Han, et al. ∙

research

∙ 01/07/2021

On the Convergence of Tsetlin Machines for the XOR Operator

The Tsetlin Machine (TM) is a novel machine learning algorithm with seve...

Lei Jiao, et al. ∙

research

∙ 11/13/2020

Affinely representable lattices, stable matchings, and choice functions

Birkhoff's representation theorem (Birkhoff, 1937) defines a bijection b...

Yuri Faenza, et al. ∙

research

∙ 10/17/2020

Finding Physical Adversarial Examples for Autonomous Driving with Fast and Differentiable Image Compositing

There is considerable evidence that deep neural networks are vulnerable ...

Jinghan Yang, et al. ∙

research

∙ 07/28/2020

On the Convergence of Tsetlin Machines for the IDENTITY- and NOT Operators

The Tsetlin Machine (TM) is a recent machine learning algorithm with sev...

Xuan Zhang, et al. ∙

research

∙ 04/22/2020

Impact of Bias on School Admissions and Targeted Interventions

There is an inherent problem in the way students are evaluated - be it s...

Yuri Faenza, et al. ∙

research

∙ 02/22/2020

Machine Translation System Selection from Bandit Feedback

Adapting machine translation systems in the real world is a difficult pr...

Jason Naradowsky, et al. ∙

research

∙ 01/16/2020

OralCam: Enabling Self-Examination and Awareness of Oral Health Using a Smartphone Camera

Due to a lack of medical resources or oral health awareness, oral diseas...

Yuan Liang, et al. ∙

research

∙ 01/16/2020

OralCam: Enabling Self-Examination and Awareness ofOral Health Using a Smartphone Camera

Due to a lack of medical resources or oral health awareness, oral diseas...

Yuan Liang, et al. ∙

research

∙ 12/30/2019

RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing

Personalized recommendation systems leverage deep learning models and ac...

Liu Ke, et al. ∙

research

∙ 12/17/2019

Quaternion Product Units for Deep Learning on 3D Rotation Groups

We propose a novel quaternion product unit (QPU) to represent data on 3D...

Xuan Zhang, et al. ∙

research

∙ 11/28/2019

Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices

Recent works propose neural network- (NN-) inspired analog-to-digital co...

Weidong Cao, et al. ∙

research

∙ 10/02/2019

Attacking Vision-based Perception in End-to-End Autonomous Driving Models

Recent advances in machine learning, especially techniques such as deep ...

Adith Boloor, et al. ∙

research

∙ 08/01/2019

Evaluating Ordering Strategies of Star Glyph Axes

Star glyphs are a well-researched visualization technique to represent m...

Matthias Miller, et al. ∙

research

∙ 06/06/2019

The Architectural Implications of Facebook's DNN-based Personalized Recommendation

The widespread application of deep learning has changed the landscape of...

Udit Gupta, et al. ∙

research

∙ 05/14/2019

Curriculum Learning for Domain Adaptation in Neural Machine Translation

We introduce a curriculum learning approach to adapt generic neural mach...

Xuan Zhang, et al. ∙

research

∙ 05/10/2019

A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks

In this paper, we apply a new promising tool for pattern classification,...

K. Darshana Abeyrathna, et al. ∙

research

∙ 03/12/2019

Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models

Recent advances in machine learning, especially techniques such as deep ...

Adith Boloor, et al. ∙

research

∙ 11/02/2018

An Empirical Exploration of Curriculum Learning for Neural Machine Translation

Machine translation systems based on deep neural networks are expensive ...

Xuan Zhang, et al. ∙

research

∙ 10/16/2018

SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification

Holistic person re-identification (ReID) has received extensive study in...

Xing Fan, et al. ∙

research

∙ 09/23/2018

Legal Assignments and fast EADAM with consent via classical theory of stable matchings

Gale and Shapley's college admission problem and concept of stability (G...

Yuri Faenza, et al. ∙

research

∙ 07/18/2018

Robust Distributed Compression of Symmetrically Correlated Gaussian Sources

Consider a lossy compression system with ℓ distributed encoders and a ce...

Yizhong Wang, et al. ∙

research

∙ 05/21/2018

AxTrain: Hardware-Oriented Neural Network Training for Approximate Inference

The intrinsic error tolerance of neural network (NN) makes approximate c...

Xin He, et al. ∙

research

∙ 12/27/2017

Multi-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project

Although many methods perform well in single camera tracking, multi-came...

Zhimeng Zhang, et al. ∙

research

∙ 11/22/2017

AlignedReID: Surpassing Human-Level Performance in Person Re-Identification

In this paper, we propose a novel method called AlignedReID that extract...

Xuan Zhang, et al. ∙

Xuan Zhang

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