Search Results for author: Tianyu Zhang

Found 25 papers, 11 papers with code

Unsupervised Hashing via Similarity Distribution Calibration

1 code implementation15 Feb 2023 Kam Woh Ng, Xiatian Zhu, Jiun Tian Hoe, Chee Seng Chan, Tianyu Zhang, Yi-Zhe Song, Tao Xiang

Instead of matching individual pairwise similarity scores, SDC aligns the hash code similarity distribution towards a calibration distribution (e. g., beta distribution) with sufficient spread across the entire similarity capacity/range, to alleviate the similarity collapse problem.

Image Retrieval Retrieval

IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data

no code implementations3 Feb 2023 Tianyu Zhang, Tao Tan, Luyi Han, Xin Wang, Yuan Gao, Jonas Teuwen, Regina Beets-Tan, Ritse Mann

Then the multi-parameter fusion with attention module enables the interaction of the encoded information from different parameters through a set of algorithmic strategies, and applies different weights to the information through the attention mechanism after information fusion to obtain refined representation information.

Lesion Classification Lesion Detection

Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRI

1 code implementation1 Feb 2023 Luyi Han, Tao Tan, Tianyu Zhang, Yunzhi Huang, Xin Wang, Yuan Gao, Jonas Teuwen, Ritse Mann

Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences.

Representation Learning

Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads

no code implementations6 Jan 2023 Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry

To integrate high amounts of renewable energy resources, electrical power grids must be able to cope with high amplitude, fast timescale variations in power generation.

Multi-agent Reinforcement Learning reinforcement-learning +1

SGDraw: Scene Graph Drawing Interface Using Object-Oriented Representation

no code implementations30 Nov 2022 Tianyu Zhang, Xusheng Du, Chia-Ming Chang, Xi Yang, Haoran Xie

However, it is difficult to draw a proper scene graph for image retrieval, image generation, and multi-modal applications.

Graph Generation Image Generation +4

Data-Driven Deep Supervision for Skin Lesion Classification

no code implementations4 Sep 2022 Suraj Mishra, Yizhe Zhang, Li Zhang, Tianyu Zhang, X. Sharon Hu, Danny Z. Chen

Specifically, we analyze the convolutional network's behavior (field-of-view) to find the location of deep supervision for improved feature extraction.

Classification Lesion Classification +1

AI for Global Climate Cooperation: Modeling Global Climate Negotiations, Agreements, and Long-Term Cooperation in RICE-N

1 code implementation15 Aug 2022 Tianyu Zhang, Andrew Williams, Soham Phade, Sunil Srinivasa, Yang Zhang, Prateek Gupta, Yoshua Bengio, Stephan Zheng

To facilitate this research, here we introduce RICE-N, a multi-region integrated assessment model that simulates the global climate and economy, and which can be used to design and evaluate the strategic outcomes for different negotiation and agreement frameworks.

Ethics Multi-agent Reinforcement Learning

Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch

no code implementations14 Jun 2022 Tianyu Zhang, Amin Banitalebi-Dehkordi, Yong Zhang

We propose a new approach for solving the data labeling and inference latency issues in combinatorial optimization based on the use of the reinforcement learning (RL) paradigm.

BIG-bench Machine Learning Combinatorial Optimization +4

Biological Sequence Design with GFlowNets

1 code implementation2 Mar 2022 Moksh Jain, Emmanuel Bengio, Alex-Hernandez Garcia, Jarrid Rector-Brooks, Bonaventure F. P. Dossou, Chanakya Ekbote, Jie Fu, Tianyu Zhang, Micheal Kilgour, Dinghuai Zhang, Lena Simine, Payel Das, Yoshua Bengio

In this work, we propose an active learning algorithm leveraging epistemic uncertainty estimation and the recently proposed GFlowNets as a generator of diverse candidate solutions, with the objective to obtain a diverse batch of useful (as defined by some utility function, for example, the predicted anti-microbial activity of a peptide) and informative candidates after each round.

Active Learning

FQ-ViT: Post-Training Quantization for Fully Quantized Vision Transformer

1 code implementation27 Nov 2021 Yang Lin, Tianyu Zhang, Peiqin Sun, Zheng Li, Shuchang Zhou

Network quantization significantly reduces model inference complexity and has been widely used in real-world deployments.

Quantization

On the Optimality of Nuclear-norm-based Matrix Completion for Problems with Smooth Non-linear Structure

no code implementations5 May 2021 Yunhua Xiang, Tianyu Zhang, Xu Wang, Ali Shojaie, Noah Simon

Originally developed for imputing missing entries in low rank, or approximately low rank matrices, matrix completion has proven widely effective in many problems where there is no reason to assume low-dimensional linear structure in the underlying matrix, as would be imposed by rank constraints.

Matrix Completion

Ternary Hashing

no code implementations16 Mar 2021 Chang Liu, Lixin Fan, Kam Woh Ng, Yilun Jin, Ce Ju, Tianyu Zhang, Chee Seng Chan, Qiang Yang

This paper proposes a novel ternary hash encoding for learning to hash methods, which provides a principled more efficient coding scheme with performances better than those of the state-of-the-art binary hashing counterparts.

Retrieval

Learning Contextualized Knowledge Graph Structures for Commonsense Reasoning

no code implementations1 Jan 2021 Jun Yan, Mrigank Raman, Tianyu Zhang, Ryan Rossi, Handong Zhao, Sungchul Kim, Nedim Lipka, Xiang Ren

Recently, neural-symbolic architectures have achieved success on commonsense reasoning through effectively encoding relational structures retrieved from external knowledge graphs (KGs) and obtained state-of-the-art results in tasks such as (commonsense) question answering and natural language inference.

Knowledge Graphs Natural Language Inference +1

UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identification

1 code implementation CVPR 2021 Tianyu Zhang, Lingxi Xie, Longhui Wei, Zijie Zhuang, Yongfei Zhang, Bo Li, Qi Tian

The main difficulty of person re-identification (ReID) lies in collecting annotated data and transferring the model across different domains.

Domain Adaptation Image Generation +1

A robust solution of a statistical inverse problem in multiscale computational mechanics using an artificial neural network

no code implementations16 Nov 2020 Florent Pled, Christophe Desceliers, Tianyu Zhang

An initial database made up with input and target data is first generated from the computational model, from which a processed database is deduced by conditioning the input data with respect to the target data using the nonparametric statistics.

Neural Networks Weights Quantization: Target None-retraining Ternary (TNT)

no code implementations18 Dec 2019 Tianyu Zhang, Lei Zhu, Qian Zhao, Kilho Shin

Quantization of weights of deep neural networks (DNN) has proven to be an effective solution for the purpose of implementing DNNs on edge devices such as mobiles, ASICs and FPGAs, because they have no sufficient resources to support computation involving millions of high precision weights and multiply-accumulate operations.

Quantization

Background Segmentation for Vehicle Re-Identification

no code implementations15 Oct 2019 Mingjie Wu, Yongfei Zhang, Tianyu Zhang, Wen-qi Zhang

Vehicle re-identification (Re-ID) is very important in intelligent transportation and video surveillance. Prior works focus on extracting discriminative features from visual appearance of vehicles or using visual-spatio-temporal information. However, background interference in vehicle re-identification have not been explored. In the actual large-scale spatio-temporal scenes, the same vehicle usually appears in different backgrounds while different vehicles might appear in the same background, which will seriously affect the re-identification performance.

Vehicle Re-Identification

Single Camera Training for Person Re-identification

1 code implementation24 Sep 2019 Tianyu Zhang, Lingxi Xie, Longhui Wei, Yongfei Zhang, Bo Li, Qi Tian

Differently, this paper investigates ReID in an unexplored single-camera-training (SCT) setting, where each person in the training set appears in only one camera.

Metric Learning Person Re-Identification

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