Search Results for author: Kai Wang

Found 193 papers, 89 papers with code

EasyTrack: Efficient and Compact One-stream 3D Point Clouds Tracker

no code implementations9 Apr 2024 Baojie Fan, Wuyang Zhou, Kai Wang, Shijun Zhou, Fengyu Xu, Jiandong Tian

Most of 3D single object trackers (SOT) in point clouds follow the two-stream multi-stage 3D Siamese or motion tracking paradigms, which process the template and search area point clouds with two parallel branches, built on supervised point cloud backbones.

TCAN: Text-oriented Cross Attention Network for Multimodal Sentiment Analysis

no code implementations6 Apr 2024 Ming Zhou, Weize Quan, Ziqi Zhou, Kai Wang, Tong Wang, Dong-Ming Yan

Motivated by these insights, we introduce a Text-oriented Cross-Attention Network (TCAN), emphasizing the predominant role of the text modality in MSA.

Multimodal Sentiment Analysis Representation Learning

A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation

no code implementations4 Apr 2024 Yin Li, Qi Chen, Kai Wang, Meige Li, Liping Si, Yingwei Guo, Yu Xiong, Qixing Wang, Yang Qin, Ling Xu, Patrick van der Smagt, Jun Tang, Nutan Chen

Multi-modality magnetic resonance imaging data with various sequences facilitate the early diagnosis, tumor segmentation, and disease staging in the management of nasopharyngeal carcinoma (NPC).

Management Tumor Segmentation

GNSS Spoofing Detection by Crowdsourcing Double Differential Pseudorange Spatial Distribution

no code implementations3 Apr 2024 Xin Chen, Kai Wang

It is widely known that spoofing is a major threat that adversely impacts the reliability and accuracy of GNSS applications.

Assessing the Utility of Large Language Models for Phenotype-Driven Gene Prioritization in Rare Genetic Disorder Diagnosis

no code implementations21 Mar 2024 Junyoung Kim, Jingye Yang, Kai Wang, Chunhua Weng, Cong Liu

A similar increasing trend was observed for the task completion rate, with complicated prompts more likely to increase task completeness in models smaller than GPT-4.

Knowledge Graphs

Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation

1 code implementation18 Mar 2024 Wangbo Zhao, Jiasheng Tang, Yizeng Han, Yibing Song, Kai Wang, Gao Huang, Fan Wang, Yang You

Existing parameter-efficient fine-tuning (PEFT) methods have achieved significant success on vision transformers (ViTs) adaptation by improving parameter efficiency.

Semantic Segmentation Video Recognition

DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting

no code implementations5 Mar 2024 Hao Wu, Haomin Wen, Guibin Zhang, Yutong Xia, Kai Wang, Yuxuan Liang, Yu Zheng, Kun Wang

In this paper, we introduce for the first time the concept of spatio-temporal data dynamic sparse training and are committed to adaptively, dynamically filtering important sensor distributions.

Spatio-Temporal Forecasting

Difference Learning for Air Quality Forecasting Transport Emulation

no code implementations22 Feb 2024 Reed River Chen, Christopher Ribaudo, Jennifer Sleeman, Chace Ashcraft, Collin Kofroth, Marisa Hughes, Ivanka Stajner, Kevin Viner, Kai Wang

Due to a recent increase in extreme air quality events, both globally and locally in the United States, finer resolution air quality forecasting guidance is needed to effectively adapt to these events.

Neural Network Diffusion

1 code implementation20 Feb 2024 Kai Wang, Zhaopan Xu, Yukun Zhou, Zelin Zang, Trevor Darrell, Zhuang Liu, Yang You

The autoencoder extracts latent representations of a subset of the trained network parameters.

LLM as Prompter: Low-resource Inductive Reasoning on Arbitrary Knowledge Graphs

no code implementations19 Feb 2024 Kai Wang, Yuwei Xu, Zhiyong Wu, Siqiang Luo

Knowledge Graph (KG) inductive reasoning, which aims to infer missing facts from new KGs that are not seen during training, has been widely adopted in various applications.

Knowledge Graphs

Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching

1 code implementation7 Feb 2024 Tianle Zhang, Yuchen Zhang, Kun Wang, Kai Wang, Beining Yang, Kaipeng Zhang, Wenqi Shao, Ping Liu, Joey Tianyi Zhou, Yang You

Training on large-scale graphs has achieved remarkable results in graph representation learning, but its cost and storage have raised growing concerns.

Graph Representation Learning

Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching

1 code implementation7 Feb 2024 Yuchen Zhang, Tianle Zhang, Kai Wang, Ziyao Guo, Yuxuan Liang, Xavier Bresson, Wei Jin, Yang You

Specifically, we employ a curriculum learning strategy to train expert trajectories with more diverse supervision signals from the original graph, and then effectively transfer the information into the condensed graph with expanding window matching.

Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness

no code implementations2 Feb 2024 Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen

Specifically, GST initially constructs a topology & semantic anchor at a low training cost, followed by performing dynamic sparse training to align the sparse graph with the anchor.

Adversarial Defense Graph Learning

Sequential Model for Predicting Patient Adherence in Subcutaneous Immunotherapy for Allergic Rhinitis

1 code implementation21 Jan 2024 Yin Li, Yu Xiong, Wenxin Fan, Kai Wang, Qingqing Yu, Liping Si, Patrick van der Smagt, Jun Tang, Nutan Chen

Conclusion: We creatively apply sequential models in the long-term management of SCIT with promising accuracy in the prediction of SCIT nonadherence in Allergic Rhinitis (AR) patients.

Management

Advancing Large Multi-modal Models with Explicit Chain-of-Reasoning and Visual Question Generation

no code implementations18 Jan 2024 Kohei Uehara, Nabarun Goswami, Hanqin Wang, Toshiaki Baba, Kohtaro Tanaka, Tomohiro Hashimoto, Kai Wang, Rei Ito, Takagi Naoya, Ryo Umagami, Yingyi Wen, Tanachai Anakewat, Tatsuya Harada

The increasing demand for intelligent systems capable of interpreting and reasoning about visual content requires the development of Large Multi-Modal Models (LMMs) that are not only accurate but also have explicit reasoning capabilities.

Language Modelling Large Language Model +2

Understanding YTHDF2-mediated mRNA Degradation By m6A-BERT-Deg

1 code implementation15 Jan 2024 Ting-He Zhang, Sumin Jo, Michelle Zhang, Kai Wang, Shou-Jiang Gao, Yufei Huang

N6-methyladenosine (m6A) is the most abundant mRNA modification within mammalian cells, holding pivotal significance in the regulation of mRNA stability, translation, and splicing.

Must: Maximizing Latent Capacity of Spatial Transcriptomics Data

1 code implementation15 Jan 2024 Zelin Zang, Liangyu Li, Yongjie Xu, Chenrui Duan, Kai Wang, Yang You, Yi Sun, Stan Z. Li

MuST integrates the multi-modality information contained in the ST data effectively into a uniform latent space to provide a foundation for all the downstream tasks.

Mutual Information as Intrinsic Reward of Reinforcement Learning Agents for On-demand Ride Pooling

no code implementations23 Dec 2023 Xianjie Zhang, Jiahao Sun, Chen Gong, Kai Wang, Yifei Cao, Hao Chen, Yu Liu

The emergence of on-demand ride pooling services allows each vehicle to serve multiple passengers at a time, thus increasing drivers' income and enabling passengers to travel at lower prices than taxi/car on-demand services (only one passenger can be assigned to a car at a time like UberX and Lyft).

Reinforcement Learning (RL)

GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Texts

no code implementations23 Dec 2023 Da Wu, Jingye Yang, Cong Liu, Tzung-Chien Hsieh, Elaine Marchi, Justin Blair, Peter Krawitz, Chunhua Weng, Wendy Chung, Gholson J. Lyon, Ian D. Krantz, Jennifer M. Kalish, Kai Wang

Many rare genetic diseases have distinctive facial features, which can be used by artificial intelligence algorithms to facilitate clinical diagnosis, in prioritizing candidate diseases to be further examined by lab tests or genetic assays, or in helping the phenotype-driven reinterpretation of genome/exome sequencing data.

Not All Large Language Models (LLMs) Succumb to the "Reversal Curse": A Comparative Study of Deductive Logical Reasoning in BERT and GPT Models

no code implementations6 Dec 2023 Jingye Yang, Da Wu, Kai Wang

The "Reversal Curse" refers to the scenario where auto-regressive decoder large language models (LLMs), such as ChatGPT, trained on "A is B" fail to learn "B is A", demonstrating a basic failure of logical deduction.

Knowledge Graphs Logical Reasoning

MLLMs-Augmented Visual-Language Representation Learning

1 code implementation30 Nov 2023 Yanqing Liu, Kai Wang, Wenqi Shao, Ping Luo, Yu Qiao, Mike Zheng Shou, Kaipeng Zhang, Yang You

Visual-language pre-training has achieved remarkable success in many multi-modal tasks, largely attributed to the availability of large-scale image-text datasets.

Representation Learning Retrieval +1

Scaling User Modeling: Large-scale Online User Representations for Ads Personalization in Meta

no code implementations16 Nov 2023 Wei zhang, Dai Li, Chen Liang, Fang Zhou, Zhongke Zhang, Xuewei Wang, Ru Li, Yi Zhou, Yaning Huang, Dong Liang, Kai Wang, Zhangyuan Wang, Zhengxing Chen, Min Li, Fenggang Wu, Minghai Chen, Huayu Li, Yunnan Wu, Zhan Shu, Mindi Yuan, Sri Reddy

To address these challenges, we present Scaling User Modeling (SUM), a framework widely deployed in Meta's ads ranking system, designed to facilitate efficient and scalable sharing of online user representation across hundreds of ads models.

Representation Learning

Towards Long-term Annotators: A Supervised Label Aggregation Baseline

no code implementations15 Nov 2023 Haoyu Liu, Fei Wang, Minmin Lin, Runze Wu, Renyu Zhu, Shiwei Zhao, Kai Wang, Tangjie Lv, Changjie Fan

These annotators could leave substantial historical annotation records on the crowdsourcing platforms, which can benefit label aggregation, but are ignored by previous works.

LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion Detection

1 code implementation14 Nov 2023 Aiheng Zhang, Kai Wang, Bailing Wang, Yulei Wu

Through experiments, we prove that LiPar has great detection performance, running efficiency, and lightweight model size, which can be well adapted to the in-vehicle environment practically and protect the in-vehicle CAN bus security.

Cloud Computing Network Intrusion Detection

Effective In-vehicle Intrusion Detection via Multi-view Statistical Graph Learning on CAN Messages

1 code implementation13 Nov 2023 Kai Wang, Qiguang Jiang, Bailing Wang, Yongzheng Zhang, Yulei Wu

In this paper, we propose StatGraph: an Effective Multi-view Statistical Graph Learning Intrusion Detection to implement the fine-grained intrusion detection.

Graph Learning Intrusion Detection

IterInv: Iterative Inversion for Pixel-Level T2I Models

1 code implementation30 Oct 2023 Chuanming Tang, Kai Wang, Joost Van de Weijer

Based on this observation, we develop an iterative inversion (IterInv) technique for this category of T2I models and verify IterInv with the open-source DeepFloyd-IF model. Specifically, IterInv employ NTI as the inversion and reconstruction of low-resolution image generation.

Super-Resolution

Exploiting Image-Related Inductive Biases in Single-Branch Visual Tracking

no code implementations30 Oct 2023 Chuanming Tang, Kai Wang, Joost Van de Weijer, Jianlin Zhang, YongMei Huang

Moreover, the effectiveness of discriminative trackers remains constrained due to the adoption of the dual-branch pipeline.

Visual Tracking

DREAM+: Efficient Dataset Distillation by Bidirectional Representative Matching

1 code implementation23 Oct 2023 Yanqing Liu, Jianyang Gu, Kai Wang, Zheng Zhu, Kaipeng Zhang, Wei Jiang, Yang You

Dataset distillation plays a crucial role in creating compact datasets with similar training performance compared with original large-scale ones.

Transfer Learning

PRIOR: Personalized Prior for Reactivating the Information Overlooked in Federated Learning

1 code implementation13 Oct 2023 Mingjia Shi, Yuhao Zhou, Kai Wang, Huaizheng Zhang, Shudong Huang, Qing Ye, Jiangcheng Lv

Personalized FL (PFL) addresses this by synthesizing personalized models from a global model via training on local data.

Federated Learning

Does Graph Distillation See Like Vision Dataset Counterpart?

2 code implementations NeurIPS 2023 Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, JianXin Li

We validate the proposed SGDD across 9 datasets and achieve state-of-the-art results on all of them: for example, on the YelpChi dataset, our approach maintains 98. 6% test accuracy of training on the original graph dataset with 1, 000 times saving on the scale of the graph.

Anomaly Detection Graph Representation Learning +1

Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching

1 code implementation9 Oct 2023 Ziyao Guo, Kai Wang, George Cazenavette, Hui Li, Kaipeng Zhang, Yang You

The ultimate goal of Dataset Distillation is to synthesize a small synthetic dataset such that a model trained on this synthetic set will perform equally well as a model trained on the full, real dataset.

Can pre-trained models assist in dataset distillation?

1 code implementation5 Oct 2023 Yao Lu, Xuguang Chen, Yuchen Zhang, Jianyang Gu, Tianle Zhang, Yifan Zhang, Xiaoniu Yang, Qi Xuan, Kai Wang, Yang You

Dataset Distillation (DD) is a prominent technique that encapsulates knowledge from a large-scale original dataset into a small synthetic dataset for efficient training.

Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing

1 code implementation NeurIPS 2023 Kai Wang, Fei Yang, Shiqi Yang, Muhammad Atif Butt, Joost Van de Weijer

Large-scale text-to-image generative models have been a ground-breaking development in generative AI, with diffusion models showing their astounding ability to synthesize convincing images following an input text prompt.

Text-based Image Editing

Multi-user beamforming in RIS-aided communications and experimental validations

no code implementations18 Sep 2023 Zhibo Zhou, Haifan Yin, Li Tan, Ruikun Zhang, Kai Wang, Yingzhuang Liu

To generate the reflection coefficients with the aim of maximizing the spectral efficiency, we propose a quadratic transform-based low-rank multi-user beamforming (QTLM) algorithm.

Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning

1 code implementation12 Sep 2023 Alex Gomez-Villa, Bartlomiej Twardowski, Kai Wang, Joost Van de Weijer

In the second phase, we combine this new knowledge with the previous network in an adaptation-retrospection phase to avoid forgetting and initialize a new expert with the knowledge of the old network.

Representation Learning Self-Supervised Learning +1

Region Generation and Assessment Network for Occluded Person Re-Identification

no code implementations7 Sep 2023 Shuting He, Weihua Chen, Kai Wang, Hao Luo, Fan Wang, Wei Jiang, Henghui Ding

Then, to measure the importance of each generated region, we introduce a Region Assessment Module (RAM) that assigns confidence scores to different regions and reduces the negative impact of the occlusion regions by lower scores.

Person Re-Identification

Recurrence-Free Survival Prediction for Anal Squamous Cell Carcinoma Chemoradiotherapy using Planning CT-based Radiomics Model

no code implementations5 Sep 2023 Shanshan Tang, Kai Wang, David Hein, Gloria Lin, Nina N. Sanford, Jing Wang

Conclusions: A treatment planning CT based radiomics and clinical combined model had improved prognostic performance in predicting RFS for ASCC patients treated with CRT as compared to a model using clinical features only.

feature selection Survival Prediction

ScrollNet: Dynamic Weight Importance for Continual Learning

1 code implementation31 Aug 2023 Fei Yang, Kai Wang, Joost Van de Weijer

The importance of weights for each task can be determined either explicitly through learning a task-specific mask during training (e. g., parameter isolation-based approaches) or implicitly by introducing a regularization term (e. g., regularization-based approaches).

Continual Learning

Dataset Quantization

1 code implementation ICCV 2023 Daquan Zhou, Kai Wang, Jianyang Gu, Xiangyu Peng, Dongze Lian, Yifan Zhang, Yang You, Jiashi Feng

Extensive experiments demonstrate that DQ is able to generate condensed small datasets for training unseen network architectures with state-of-the-art compression ratios for lossless model training.

object-detection Object Detection +2

The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive field

no code implementations19 Aug 2023 Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Xiaojiang Peng, Yuxuan Liang, Yang Wang

Despite Graph Neural Networks demonstrating considerable promise in graph representation learning tasks, GNNs predominantly face significant issues with over-fitting and over-smoothing as they go deeper as models of computer vision realm.

Graph Representation Learning

Enhancing Phenotype Recognition in Clinical Notes Using Large Language Models: PhenoBCBERT and PhenoGPT

1 code implementation11 Aug 2023 Jingye Yang, Cong Liu, Wendy Deng, Da Wu, Chunhua Weng, Yunyun Zhou, Kai Wang

We hypothesize that large language models (LLMs) based on the transformer architecture can enable automated detection of clinical phenotype terms, including terms not documented in the HPO.

Negation

DVPT: Dynamic Visual Prompt Tuning of Large Pre-trained Models for Medical Image Analysis

no code implementations19 Jul 2023 Along He, Kai Wang, Zhihong Wang, Tao Li, Huazhu Fu

Firstly, the frozen features are transformed by an lightweight bottleneck layer to learn the domain-specific distribution of downstream medical tasks, and then a few learnable visual prompts are used as dynamic queries and then conduct cross-attention with the transformed features, attempting to acquire sample-specific knowledge that are suitable for each sample.

Visual Prompt Tuning

Evidential Detection and Tracking Collaboration: New Problem, Benchmark and Algorithm for Robust Anti-UAV System

1 code implementation27 Jun 2023 Xue-Feng Zhu, Tianyang Xu, Jian Zhao, Jia-Wei Liu, Kai Wang, Gang Wang, Jianan Li, Qiang Wang, Lei Jin, Zheng Zhu, Junliang Xing, Xiao-Jun Wu

Still, previous works have simplified such an anti-UAV task as a tracking problem, where the prior information of UAVs is always provided; such a scheme fails in real-world anti-UAV tasks (i. e. complex scenes, indeterminate-appear and -reappear UAVs, and real-time UAV surveillance).

Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?

no code implementations30 May 2023 Jianfei Yang, Hanjie Qian, Yuecong Xu, Kai Wang, Lihua Xie

Unsupervised domain adaptation (UDA) involves adapting a model trained on a label-rich source domain to an unlabeled target domain.

Unsupervised Domain Adaptation

Generating Driving Scenes with Diffusion

no code implementations29 May 2023 Ethan Pronovost, Kai Wang, Nick Roy

In this paper we describe a learned method of traffic scene generation designed to simulate the output of the perception system of a self-driving car.

object-detection Object Detection +1

Summarizing Stream Data for Memory-Constrained Online Continual Learning

2 code implementations26 May 2023 Jianyang Gu, Kai Wang, Wei Jiang, Yang You

Through maintaining the consistency of training gradients and relationship to the past tasks, the summarized samples are more representative for the stream data compared to the original images.

Continual Learning Informativeness

SAMScore: A Semantic Structural Similarity Metric for Image Translation Evaluation

1 code implementation24 May 2023 Yunxiang Li, Meixu Chen, Wenxuan Yang, Kai Wang, Jun Ma, Alan C. Bovik, You Zhang

Image translation has wide applications, such as style transfer and modality conversion, usually aiming to generate images having both high degrees of realism and faithfulness.

Semantic Similarity Semantic Textual Similarity +2

River of No Return: Graph Percolation Embeddings for Efficient Knowledge Graph Reasoning

no code implementations17 May 2023 Kai Wang, Siqiang Luo, Dan Lin

We study Graph Neural Networks (GNNs)-based embedding techniques for knowledge graph (KG) reasoning.

A Soft Coordination Method of Heterogeneous Devices in Distribution System Voltage Control

no code implementations4 May 2023 Licheng Wang, Tao Wang, Gang Huang, Ruifeng Yan, Kai Wang, Youbing Zhang, Shijie Cheng

The proposed method achieves the soft coordination by establishing a modified actor-critic algorithm to train a proxy model of inverters.

Decision Making

Zero-shot Generative Model Adaptation via Image-specific Prompt Learning

1 code implementation CVPR 2023 Jiayi Guo, Chaofei Wang, You Wu, Eric Zhang, Kai Wang, Xingqian Xu, Shiji Song, Humphrey Shi, Gao Huang

Recently, CLIP-guided image synthesis has shown appealing performance on adapting a pre-trained source-domain generator to an unseen target domain.

Image Generation

Motion-R3: Fast and Accurate Motion Annotation via Representation-based Representativeness Ranking

no code implementations4 Apr 2023 Jubo Yu, Tianxiang Ren, Shihui Guo, Fengyi Fang, Kai Wang, Zijiao Zeng, Yazhan Zhang, Andreas Aristidou, Yipeng Qin

In this paper, we follow a data-centric philosophy and propose a novel motion annotation method based on the inherent representativeness of motion data in a given dataset.

Philosophy

Classification of integers based on residue classes via modern deep learning algorithms

1 code implementation3 Apr 2023 Da Wu, Jingye Yang, Mian Umair Ahsan, Kai Wang

Judging whether an integer can be divided by prime numbers such as 2 or 3 may appear trivial to human beings, but can be less straightforward for computers.

AutoML Feature Engineering

Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models

1 code implementation30 Mar 2023 Eric Zhang, Kai Wang, Xingqian Xu, Zhangyang Wang, Humphrey Shi

The unlearning problem of deep learning models, once primarily an academic concern, has become a prevalent issue in the industry.

Disentanglement Memorization +1

BiCro: Noisy Correspondence Rectification for Multi-modality Data via Bi-directional Cross-modal Similarity Consistency

1 code implementation CVPR 2023 Shuo Yang, Zhaopan Xu, Kai Wang, Yang You, Hongxun Yao, Tongliang Liu, Min Xu

As one of the most fundamental techniques in multimodal learning, cross-modal matching aims to project various sensory modalities into a shared feature space.

Image-text matching Text Matching

CSSL-MHTR: Continual Self-Supervised Learning for Scalable Multi-script Handwritten Text Recognition

no code implementations16 Mar 2023 Marwa Dhiaf, Mohamed Ali Souibgui, Kai Wang, Yuyang Liu, Yousri Kessentini, Alicia Fornés, Ahmed Cheikh Rouhou

In this paper, we explore the potential of continual self-supervised learning to alleviate the catastrophic forgetting problem in handwritten text recognition, as an example of sequence recognition.

Handwritten Text Recognition Self-Supervised Learning

MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReID

1 code implementation CVPR 2023 Jianyang Gu, Kai Wang, Hao Luo, Chen Chen, Wei Jiang, Yuqiang Fang, Shanghang Zhang, Yang You, Jian Zhao

Neural Architecture Search (NAS) has been increasingly appealing to the society of object Re-Identification (ReID), for that task-specific architectures significantly improve the retrieval performance.

Image Classification Neural Architecture Search +3

Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models

1 code implementation ICCV 2023 Zangwei Zheng, Mingyuan Ma, Kai Wang, Ziheng Qin, Xiangyu Yue, Yang You

To address this challenge, we propose a novel method ZSCL to prevent zero-shot transfer degradation in the continual learning of vision-language models in both feature and parameter space.

Class Incremental Learning Incremental Learning

DiM: Distilling Dataset into Generative Model

2 code implementations8 Mar 2023 Kai Wang, Jianyang Gu, Daquan Zhou, Zheng Zhu, Wei Jiang, Yang You

To the best of our knowledge, we are the first to achieve higher accuracy on complex architectures than simple ones, such as 75. 1\% with ResNet-18 and 72. 6\% with ConvNet-3 on ten images per class of CIFAR-10.

InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

1 code implementation8 Mar 2023 Ziheng Qin, Kai Wang, Zangwei Zheng, Jianyang Gu, Xiangyu Peng, Zhaopan Xu, Daquan Zhou, Lei Shang, Baigui Sun, Xuansong Xie, Yang You

To solve this problem, we propose \textbf{InfoBatch}, a novel framework aiming to achieve lossless training acceleration by unbiased dynamic data pruning.

Semantic Segmentation

DREAM: Efficient Dataset Distillation by Representative Matching

2 code implementations ICCV 2023 Yanqing Liu, Jianyang Gu, Kai Wang, Zheng Zhu, Wei Jiang, Yang You

Although there are various matching objectives, currently the strategy for selecting original images is limited to naive random sampling.

Bioformer: an efficient transformer language model for biomedical text mining

1 code implementation3 Feb 2023 Li Fang, Qingyu Chen, Chih-Hsuan Wei, Zhiyong Lu, Kai Wang

We thoroughly evaluated the performance of Bioformer as well as existing biomedical BERT models including BioBERT and PubMedBERT on 15 benchmark datasets of four different biomedical NLP tasks: named entity recognition, relation extraction, question answering and document classification.

Document Classification Language Modelling +5

Specialist Diffusion: Plug-and-Play Sample-Efficient Fine-Tuning of Text-to-Image Diffusion Models To Learn Any Unseen Style

no code implementations CVPR 2023 Haoming Lu, Hazarapet Tunanyan, Kai Wang, Shant Navasardyan, Zhangyang Wang, Humphrey Shi

Diffusion models have demonstrated impressive capability of text-conditioned image synthesis, and broader application horizons are emerging by personalizing those pretrained diffusion models toward generating some specialized target object or style.

Disentanglement Image Generation

CORE: Co-planarity Regularized Monocular Geometry Estimation with Weak Supervision

no code implementations ICCV 2023 Yuguang Li, Kai Wang, Hui Li, Seon-Min Rhee, Seungju Han, JiHye Kim, Min Yang, Ran Yang, Feng Zhu

Meanwhile, SANE easily establishes multi-task learning with CORE loss functions on both depth and surface normal estimation, leading to the whole performance leap.

Depth Estimation Multi-Task Learning +2

Expanding Small-Scale Datasets with Guided Imagination

1 code implementation NeurIPS 2023 Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng

Specifically, GIF conducts data imagination by optimizing the latent features of the seed data in the semantically meaningful space of the prior model, resulting in the creation of photo-realistic images with new content.

Self adaptive global-local feature enhancement for radiology report generation

no code implementations21 Nov 2022 Yuhao Wang, Kai Wang, Xiaohong Liu, Tianrun Gao, Jingyue Zhang, Guangyu Wang

Automated radiology report generation aims at automatically generating a detailed description of medical images, which can greatly alleviate the workload of radiologists and provide better medical services to remote areas.

Anatomy

Versatile Diffusion: Text, Images and Variations All in One Diffusion Model

3 code implementations ICCV 2023 Xingqian Xu, Zhangyang Wang, Eric Zhang, Kai Wang, Humphrey Shi

In this work, we expand the existing single-flow diffusion pipeline into a multi-task multimodal network, dubbed Versatile Diffusion (VD), that handles multiple flows of text-to-image, image-to-text, and variations in one unified model.

Disentanglement Image Captioning +5

Dataset Factorization for Condensation

1 code implementation NIPS 2022 Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, Xinchao Wang

In this paper, we study dataset distillation (DD), from a novel perspective and introduce a \emph{dataset factorization} approach, termed \emph{HaBa}, which is a plug-and-play strategy portable to any existing DD baseline.

Hallucination Informativeness

Dataset Distillation via Factorization

3 code implementations30 Oct 2022 Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, Xinchao Wang

In this paper, we study \xw{dataset distillation (DD)}, from a novel perspective and introduce a \emph{dataset factorization} approach, termed \emph{HaBa}, which is a plug-and-play strategy portable to any existing DD baseline.

Hallucination Informativeness

MV-HAN: A Hybrid Attentive Networks based Multi-View Learning Model for Large-scale Contents Recommendation

no code implementations14 Oct 2022 Ge Fan, Chaoyun Zhang, Kai Wang, Junyang Chen

In this paper, we introduce a novel Multi-View Approach with Hybrid Attentive Networks (MV-HAN) for contents retrieval at the matching stage of recommender systems.

MULTI-VIEW LEARNING Recommendation Systems +1

Vision-Based Defect Classification and Weight Estimation of Rice Kernels

no code implementations6 Oct 2022 Xiang Wang, Kai Wang, Xiaohong Li, Shiguo Lian

To compensate for the imbalance of different kernel numbers and classify kernels with multiple flaws accurately, we propose a multi-stage workflow which is able to locate the kernels in the captured image and classify their properties.

Attention Distillation: self-supervised vision transformer students need more guidance

1 code implementation3 Oct 2022 Kai Wang, Fei Yang, Joost Van de Weijer

In experiments on ImageNet-Subset and ImageNet-1K, we show that our method AttnDistill outperforms existing self-supervised knowledge distillation (SSKD) methods and achieves state-of-the-art k-NN accuracy compared with self-supervised learning (SSL) methods learning from scratch (with the ViT-S model).

Knowledge Distillation Self-Supervised Learning

Uncertainty estimations methods for a deep learning model to aid in clinical decision-making -- a clinician's perspective

no code implementations2 Oct 2022 Michael Dohopolski, Kai Wang, Biling Wang, Ti Bai, Dan Nguyen, David Sher, Steve Jiang, Jing Wang

Especially for smaller, single institutional datasets, it may be important to evaluate multiple estimations techniques before incorporating a model into clinical practice.

Decision Making Specificity +1

RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration

1 code implementation27 Sep 2022 Hao Yu, Ji Hou, Zheng Qin, Mahdi Saleh, Ivan Shugurov, Kai Wang, Benjamin Busam, Slobodan Ilic

More specifically, 3D structures of the whole frame are first represented by our global PPF signatures, from which structural descriptors are learned to help geometric descriptors sense the 3D world beyond local regions.

Point Cloud Registration

Recurrence-free Survival Prediction under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers

1 code implementation22 Sep 2022 Kai Wang, Yunxiang Li, Michael Dohopolski, Tao Peng, Weiguo Lu, You Zhang, Jing Wang

For Head and Neck Cancers (HNC) patient management, automatic gross tumor volume (GTV) segmentation and accurate pre-treatment cancer recurrence prediction are of great importance to assist physicians in designing personalized management plans, which have the potential to improve the treatment outcome and quality of life for HNC patients.

Management Segmentation +2

Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression

1 code implementation11 Sep 2022 Yuanchao Bai, Xianming Liu, Kai Wang, Xiangyang Ji, Xiaolin Wu, Wen Gao

In the lossless mode, the DLPR coding system first performs lossy compression and then lossless coding of residuals.

Image Compression

Prompt Vision Transformer for Domain Generalization

1 code implementation18 Aug 2022 Zangwei Zheng, Xiangyu Yue, Kai Wang, Yang You

In this paper, we propose a novel approach DoPrompt based on prompt learning to embed the knowledge of source domains in domain prompts for target domain prediction.

Domain Generalization Representation Learning

QuickSkill: Novice Skill Estimation in Online Multiplayer Games

no code implementations15 Aug 2022 Chaoyun Zhang, Kai Wang, Hao Chen, Ge Fan, Yingjie Li, Lifang Wu, Bingchao Zheng

However, the skill rating of a novice is usually inaccurate, as current matchmaking rating algorithms require considerable amount of games for learning the true skill of a new player.

Fairness

OneRing: A Simple Method for Source-free Open-partial Domain Adaptation

1 code implementation7 Jun 2022 Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost Van de Weijer

In this paper, we investigate Source-free Open-partial Domain Adaptation (SF-OPDA), which addresses the situation where there exist both domain and category shifts between source and target domains.

Domain Generalization Open Set Learning +2

Progressive Multi-scale Consistent Network for Multi-class Fundus Lesion Segmentation

2 code implementations31 May 2022 Along He, Kai Wang, Tao Li, Wang Bo, Hong Kang, Huazhu Fu

The two proposed PFF and DAB blocks can be integrated with the off-the-shelf backbone networks to address the two issues of multi-scale and feature inconsistency in the multi-class segmentation of fundus lesions, which will produce better feature representation in the feature space.

Lesion Segmentation Segmentation +1

Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors

1 code implementation28 May 2022 Jianfei Yang, Xiangyu Peng, Kai Wang, Zheng Zhu, Jiashi Feng, Lihua Xie, Yang You

Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an unlabeled target domain supervised by a black-box predictor trained on a source domain.

Domain Adaptation Knowledge Distillation

Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation

1 code implementation9 May 2022 Shiqi Yang, Yaxing Wang, Kai Wang, Shangling Jui, Joost Van de Weijer

Treating SFDA as an unsupervised clustering problem and following the intuition that local neighbors in feature space should have more similar predictions than other features, we propose to optimize an objective of prediction consistency.

Clustering Source-Free Domain Adaptation

A Novel Speech-Driven Lip-Sync Model with CNN and LSTM

no code implementations2 May 2022 Xiaohong Li, Xiang Wang, Kai Wang, Shiguo Lian

Generating synchronized and natural lip movement with speech is one of the most important tasks in creating realistic virtual characters.

Face Model speech-recognition +1

Reliable Label Correction is a Good Booster When Learning with Extremely Noisy Labels

1 code implementation30 Apr 2022 Kai Wang, Xiangyu Peng, Shuo Yang, Jianfei Yang, Zheng Zhu, Xinchao Wang, Yang You

This paradigm, however, is prone to significant degeneration under heavy label noise, as the number of clean samples is too small for conventional methods to behave well.

Learning with noisy labels

Grasping the Arrow of Time from the Singularity: Decoding Micromotion in Low-dimensional Latent Spaces from StyleGAN

1 code implementation27 Apr 2022 Qiucheng Wu, Yifan Jiang, Junru Wu, Kai Wang, Gong Zhang, Humphrey Shi, Zhangyang Wang, Shiyu Chang

To study the motion features in the latent space of StyleGAN, in this paper, we hypothesize and demonstrate that a series of meaningful, natural, and versatile small, local movements (referred to as "micromotion", such as expression, head movement, and aging effect) can be represented in low-rank spaces extracted from the latent space of a conventionally pre-trained StyleGAN-v2 model for face generation, with the guidance of proper "anchors" in the form of either short text or video clips.

Disentanglement Face Generation

Investigating Accuracy-Novelty Performance for Graph-based Collaborative Filtering

1 code implementation26 Apr 2022 Minghao Zhao, Le Wu, Yile Liang, Lei Chen, Jian Zhang, Qilin Deng, Kai Wang, Xudong Shen, Tangjie Lv, Runze Wu

While conventional CF models are known for facing the challenges of the popularity bias that favors popular items, one may wonder "Whether the existing graph-based CF models alleviate or exacerbate popularity bias of recommender systems?"

Collaborative Filtering Recommendation Systems

Smoothed Online Combinatorial Optimization Using Imperfect Predictions

no code implementations23 Apr 2022 Kai Wang, Zhao Song, Georgios Theocharous, Sridhar Mahadevan

Smoothed online combinatorial optimization considers a learner who repeatedly chooses a combinatorial decision to minimize an unknown changing cost function with a penalty on switching decisions in consecutive rounds.

Combinatorial Optimization

Deep Q-learning of global optimizer of multiply model parameters for viscoelastic imaging

no code implementations1 Apr 2022 Hongmei Zhang, Kai Wang, Yan Zhou, Shadab Momin, Xiaofeng Yang, Mostafa Fatemi, Michael F. Insana

Significance: DQMP method is promising for imaging of multiple parameters, and can be generalized to global optimization for many other complex nonconvex functions and imaging of physical parameters.

Decision Making Q-Learning

Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses

no code implementations30 Mar 2022 Sanket Shah, Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe

Decision-Focused Learning (DFL) is a paradigm for tailoring a predictive model to a downstream optimization task that uses its predictions in order to perform better on that specific task.

Decision Making

MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning

2 code implementations CVPR 2022 Shiming Chen, Ziming Hong, Guo-Sen Xie, Wenhan Yang, Qinmu Peng, Kai Wang, Jian Zhao, Xinge You

Prior works either simply align the global features of an image with its associated class semantic vector or utilize unidirectional attention to learn the limited latent semantic representations, which could not effectively discover the intrinsic semantic knowledge e. g., attribute semantics) between visual and attribute features.

Attribute Transfer Learning +1

CAFE: Learning to Condense Dataset by Aligning Features

2 code implementations CVPR 2022 Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Shuo Yang, Shuo Wang, Guan Huang, Hakan Bilen, Xinchao Wang, Yang You

Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one.

Dataset Condensation

Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health

no code implementations2 Feb 2022 Kai Wang, Shresth Verma, Aditya Mate, Sanket Shah, Aparna Taneja, Neha Madhiwalla, Aparna Hegde, Milind Tambe

To address this shortcoming, we propose a novel approach for decision-focused learning in RMAB that directly trains the predictive model to maximize the Whittle index solution quality.

Multi-Armed Bandits Scheduling

Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddings

no code implementations3 Jan 2022 Kai Wang, Yu Liu, Quan Z. Sheng

Knowledge graph embedding (KGE) has shown great potential in automatic knowledge graph (KG) completion and knowledge-driven tasks.

Contrastive Learning Knowledge Graph Embedding +1

Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms

no code implementations10 Dec 2021 Kai Wang, Xianghao Xu, Leon Lei, Selena Ling, Natalie Lindsay, Angel X. Chang, Manolis Savva, Daniel Ritchie

We then discuss different strategies for solving the problem, and design two representative pipelines: one uses available 2D floor plans to guide selection and deformation of 3D rooms; the other learns to retrieve a set of compatible 3D rooms and combine them into novel layouts.

3D Reconstruction Autonomous Navigation +2

The Shape Part Slot Machine: Contact-based Reasoning for Generating 3D Shapes from Parts

no code implementations1 Dec 2021 Kai Wang, Paul Guerrero, Vladimir Kim, Siddhartha Chaudhuri, Minhyuk Sung, Daniel Ritchie

We present the Shape Part Slot Machine, a new method for assembling novel 3D shapes from existing parts by performing contact-based reasoning.

Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition

1 code implementation9 Nov 2021 Kai Wang, Xialei Liu, Andy Bagdanov, Luis Herranz, Shangling Jui, Joost Van de Weijer

We propose an approach to IML, which we call Episodic Replay Distillation (ERD), that mixes classes from the current task with class exemplars from previous tasks when sampling episodes for meta-learning.

Continual Learning Knowledge Distillation +1

Deciphering the Language of Nature: A transformer-based language model for deleterious mutations in proteins

1 code implementation27 Oct 2021 Theodore Jiang, Li Fang, Kai Wang

In this study, we introduce MutFormer, a transformer-based model for the prediction of deleterious missense mutations, which uses reference and mutated protein sequences from the human genome as the primary features.

Language Modelling

HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification

1 code implementation21 Oct 2021 Kai Wang, Xialei Liu, Luis Herranz, Joost Van de Weijer

To overcome forgetting in this benchmark, we propose Hierarchy-Consistency Verification (HCV) as an enhancement to existing continual learning methods.

Classification Continual Learning +1

RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender System

1 code implementation18 Oct 2021 Kai Wang, Zhene Zou, Minghao Zhao, Qilin Deng, Yue Shang, Yile Liang, Runze Wu, Xudong Shen, Tangjie Lyu, Changjie Fan

In summary, the RL4RS (Reinforcement Learning for Recommender Systems), a new resource with special concerns on the reality gaps, contains two real-world datasets, data understanding tools, tuned simulation environments, related advanced RL baselines, batch RL baselines, and counterfactual policy evaluation algorithms.

Combinatorial Optimization counterfactual +3

Feudal Reinforcement Learning by Reading Manuals

no code implementations13 Oct 2021 Kai Wang, Zhonghao Wang, Mo Yu, Humphrey Shi

The manager agent is a multi-hop plan generator dealing with high-level abstract information and generating a series of sub-goals in a backward manner.

reinforcement-learning Reinforcement Learning (RL)

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning

no code implementations NeurIPS 2021 Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe

In the predict-then-optimize framework, the objective is to train a predictive model, mapping from environment features to parameters of an optimization problem, which maximizes decision quality when the optimization is subsequently solved.

Reinforcement Learning (RL)

Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning

no code implementations NeurIPS 2021 Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe

In the predict-then-optimize framework, the objective is to train a predictive model, mapping from environment features to parameters of an optimization problem, which maximizes decision quality when the optimization is subsequently solved.

Decision Making Reinforcement Learning (RL)

An Efficient Training Approach for Very Large Scale Face Recognition

1 code implementation CVPR 2022 Kai Wang, Shuo Wang, Panpan Zhang, Zhipeng Zhou, Zheng Zhu, Xiaobo Wang, Xiaojiang Peng, Baigui Sun, Hao Li, Yang You

This method adopts Dynamic Class Pool (DCP) for storing and updating the identities features dynamically, which could be regarded as a substitute for the FC layer.

 Ranked #1 on Face Verification on IJB-C (training dataset metric)

Face Recognition Face Verification

ACAE-REMIND for Online Continual Learning with Compressed Feature Replay

no code implementations18 May 2021 Kai Wang, Luis Herranz, Joost Van de Weijer

Methods are typically allowed to use a limited buffer to store some of the images in the stream.

Continual Learning

Learning to Cluster Faces via Transformer

no code implementations23 Apr 2021 Jinxing Ye, Xioajiang Peng, Baigui Sun, Kai Wang, Xiuyu Sun, Hao Li, Hanqing Wu

In this paper, we repurpose the well-known Transformer and introduce a Face Transformer for supervised face clustering.

Clustering Face Clustering +2

Continual learning in cross-modal retrieval

no code implementations14 Apr 2021 Kai Wang, Luis Herranz, Joost Van de Weijer

We found that the indexing stage pays an important role and that simply avoiding reindexing the database with updated embedding networks can lead to significant gains.

Continual Learning Cross-Modal Retrieval +2

Personalized Bundle Recommendation in Online Games

no code implementations12 Apr 2021 Qilin Deng, Kai Wang, Minghao Zhao, Zhene Zou, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen

In business domains, \textit{bundling} is one of the most important marketing strategies to conduct product promotions, which is commonly used in online e-commerce and offline retailers.

Link Prediction Marketing +1

Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation

no code implementations7 Apr 2021 Kai Wang, Zhene Zou, Qilin Deng, Runze Wu, Jianrong Tao, Changjie Fan, Liang Chen, Peng Cui

As a part of the value function, free from the sparse and high-variance reward signals, a high-capacity reward-independent world model is trained to simulate complex environmental dynamics under a certain goal.

Model-based Reinforcement Learning Recommendation Systems +2

TSTNN: Two-stage Transformer based Neural Network for Speech Enhancement in the Time Domain

no code implementations18 Mar 2021 Kai Wang, Bengbeng He, Wei-Ping Zhu

In this paper, we propose a transformer-based architecture, called two-stage transformer neural network (TSTNN) for end-to-end speech denoising in the time domain.

Denoising Speech Denoising +1

On Implicit Attribute Localization for Generalized Zero-Shot Learning

no code implementations8 Mar 2021 Shiqi Yang, Kai Wang, Luis Herranz, Joost Van de Weijer

Zero-shot learning (ZSL) aims to discriminate images from unseen classes by exploiting relations to seen classes via their attribute-based descriptions.

Attribute Generalized Zero-Shot Learning

A Benchmark of Ocular Disease Intelligent Recognition: One Shot for Multi-disease Detection

no code implementations16 Feb 2021 Ning li, Tao Li, Chunyu Hu, Kai Wang, Hong Kang

In ophthalmology, early fundus screening is an economic and effective way to prevent blindness caused by ophthalmic diseases.

Applications of Deep Learning in Fundus Images: A Review

1 code implementation25 Jan 2021 Tao Li, Wang Bo, Chunyu Hu, Hong Kang, Hanruo Liu, Kai Wang, Huazhu Fu

The use of fundus images for the early screening of eye diseases is of great clinical importance.

Image Generation Lesion Segmentation +1

AU-Guided Unsupervised Domain Adaptive Facial Expression Recognition

no code implementations18 Dec 2020 Kai Wang, Yuxin Gu, Xiaojiang Peng, Panpan Zhang, Baigui Sun, Hao Li

The domain diversities including inconsistent annotation and varied image collection conditions inevitably exist among different facial expression recognition (FER) datasets, which pose an evident challenge for adapting the FER model trained on one dataset to another one.

Facial Expression Recognition Facial Expression Recognition (FER)

Takagi topological insulator with odd $\mathcal P\mathcal T$ pairs of corner states

no code implementations17 Dec 2020 Jia-Xiao Dai, Kai Wang, Shengyuan A. Yang, Y. X. Zhao

Particularly, the global Takagi's factorization can (cannot) be done on a $3$D ($2$D) sphere.

Mesoscale and Nanoscale Physics

Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning

2 code implementations NeurIPS 2021 Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin

In this paper, we provide a theory of using graph neural networks (GNNs) for multi-node representation learning (where we are interested in learning a representation for a set of more than one node, such as link).

General Classification Graph Classification +4

Suppressing Mislabeled Data via Grouping and Self-Attention

1 code implementation ECCV 2020 Xiaojiang Peng, Kai Wang, Zhaoyang Zeng, Qing Li, Jianfei Yang, Yu Qiao

Specifically, this plug-and-play AFM first leverages a \textit{group-to-attend} module to construct groups and assign attention weights for group-wise samples, and then uses a \textit{mixup} module with the attention weights to interpolate massive noisy-suppressed samples.

Image Classification

MulDE: Multi-teacher Knowledge Distillation for Low-dimensional Knowledge Graph Embeddings

no code implementations14 Oct 2020 Kai Wang, Yu Liu, Qian Ma, Quan Z. Sheng

Link prediction based on knowledge graph embeddings (KGE) aims to predict new triples to automatically construct knowledge graphs (KGs).

Knowledge Distillation Knowledge Graph Embedding +2

A Comprehensive Review for MRF and CRF Approaches in Pathology Image Analysis

no code implementations29 Sep 2020 Yixin Li, Chen Li, Xiaoyan Li, Kai Wang, Md Mamunur Rahaman, Changhao Sun, Hao Chen, Xinran Wu, Hong Zhang, Qian Wang

In this review, we present a comprehensive overview of pathology image analysis based on the markov random fields (MRFs) and conditional random fields (CRFs), which are two popular random field models.

Dual-Mandate Patrols: Multi-Armed Bandits for Green Security

2 code implementations14 Sep 2020 Lily Xu, Elizabeth Bondi, Fei Fang, Andrew Perrault, Kai Wang, Milind Tambe

Conservation efforts in green security domains to protect wildlife and forests are constrained by the limited availability of defenders (i. e., patrollers), who must patrol vast areas to protect from attackers (e. g., poachers or illegal loggers).

Multi-Armed Bandits

Measuring galaxy abundance and clustering at high redshift from incomplete spectroscopic data: Tests on mock catalogs

1 code implementation31 Aug 2020 Jiacheng Meng, Cheng Li, Houjun Mo, Yangyao Chen, Kai Wang

We also quantify improvements expected in the PFS-like galaxy survey relative to zCOSMOS and VIPERS surveys.

Astrophysics of Galaxies

CardioLearn: A Cloud Deep Learning Service for Cardiac Disease Detection from Electrocardiogram

1 code implementation4 Jul 2020 Shenda Hong, Zhaoji Fu, Rongbo Zhou, Jie Yu, Yongkui Li, Kai Wang, Guanlin Cheng

Electrocardiogram (ECG) is one of the most convenient and non-invasive tools for monitoring peoples' heart condition, which can use for diagnosing a wide range of heart diseases, including Cardiac Arrhythmia, Acute Coronary Syndrome, et al.

Low-Resource Generation of Multi-hop Reasoning Questions

no code implementations ACL 2020 Jianxing Yu, Wei Liu, Shuang Qiu, Qinliang Su, Kai Wang, Xiaojun Quan, Jian Yin

Specifically, we first build a multi-hop generation model and guide it to satisfy the logical rationality by the reasoning chain extracted from a given text.

Machine Reading Comprehension valid

Bookworm continual learning: beyond zero-shot learning and continual learning

no code implementations26 Jun 2020 Kai Wang, Luis Herranz, Anjan Dutta, Joost Van de Weijer

We propose bookworm continual learning(BCL), a flexible setting where unseen classes can be inferred via a semantic model, and the visual model can be updated continually.

Attribute Continual Learning +1

Automatically Learning Compact Quality-aware Surrogates for Optimization Problems

2 code implementations NeurIPS 2020 Kai Wang, Bryan Wilder, Andrew Perrault, Milind Tambe

Solving optimization problems with unknown parameters often requires learning a predictive model to predict the values of the unknown parameters and then solving the problem using these values.

Portfolio Optimization

Simple and effective localized attribute representations for zero-shot learning

no code implementations10 Jun 2020 Shiqi Yang, Kai Wang, Luis Herranz, Joost Van de Weijer

Zero-shot learning (ZSL) aims to discriminate images from unseen classes by exploiting relations to seen classes via their semantic descriptions.

Attribute Zero-Shot Learning