Search Results for author: Di wu

Found 207 papers, 60 papers with code

End-to-end Graph Learning Approach for Cognitive Diagnosis of Student Tutorial

no code implementations30 Oct 2024 Fulai Yang, Di wu, Yi He, Li Tao, Xin Luo

However, existing approaches loosely consider these relationships and mechanisms by a non-end-to-end learning framework, resulting in sub-optimal feature extractions and fusions for CD.

Robot Policy Learning with Temporal Optimal Transport Reward

1 code implementation29 Oct 2024 Yuwei Fu, Haichao Zhang, Di wu, Wei Xu, Benoit Boulet

To address this issue, in this paper, we introduce the Temporal Optimal Transport (TemporalOT) reward to incorporate temporal order information for learning a more accurate OT-based proxy reward.

A Unified Solution to Diverse Heterogeneities in One-shot Federated Learning

no code implementations28 Oct 2024 Jun Bai, Yiliao Song, Di wu, Atul Sajjanhar, Yong Xiang, Wei Zhou, Xiaohui Tao, Yan Li

Specifically, a new stratified learning structure is proposed to cover data heterogeneity, and the value of each item during computation reflects model heterogeneity.

Federated Learning

BRIEF: Bridging Retrieval and Inference for Multi-hop Reasoning via Compression

1 code implementation20 Oct 2024 Yuankai Li, Jia-Chen Gu, Di wu, Kai-Wei Chang, Nanyun Peng

Based on our synthetic data built entirely by open-source models, BRIEF generates more concise summaries and enables a range of LLMs to achieve exceptional open-domain question answering (QA) performance.

In-Context Learning Long-Context Understanding +3

Trajectory Prediction for Autonomous Driving using Agent-Interaction Graph Embedding

no code implementations15 Oct 2024 Jilan Samiuddin, Benoit Boulet, Di wu

Finally, an output network comprising a Multilayer Perceptron is used to predict the trajectories utilizing the decoded states as its inputs.

Autonomous Driving Decision Making +3

LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory

1 code implementation14 Oct 2024 Di wu, Hongwei Wang, Wenhao Yu, Yuwei Zhang, Kai-Wei Chang, Dong Yu

Recent large language model (LLM)-driven chat assistant systems have integrated memory components to track user-assistant chat histories, enabling more accurate and personalized responses.

Benchmarking Large Language Model +1

Towards Homogeneous Lexical Tone Decoding from Heterogeneous Intracranial Recordings

no code implementations13 Oct 2024 Di wu, Siyuan Li, Chen Feng, Lu Cao, Yue Zhang, Jie Yang, Mohamad Sawan

To address these limitations, we introduce Homogeneity-Heterogeneity Disentangled Learning for neural Representations (H2DiLR), a novel framework that disentangles and learns both the homogeneity and heterogeneity from intracranial recordings across multiple subjects.

Representation Learning

GrabDAE: An Innovative Framework for Unsupervised Domain Adaptation Utilizing Grab-Mask and Denoise Auto-Encoder

no code implementations10 Oct 2024 Junzhou Chen, Xuan Wen, Ronghui Zhang, Bingtao Ren, Di wu, Zhigang Xu, Danwei Wang

Unsupervised Domain Adaptation (UDA) aims to adapt a model trained on a labeled source domain to an unlabeled target domain by addressing the domain shift.

Contrastive Learning Denoising +1

Direction Modulation Design for UAV Assisted by IRS with discrete phase shift

no code implementations7 Oct 2024 Maolin Li, Wei Gao, Qi Wu, Feng Shu, Cunhua Pan, Di wu

Secondly, three methods are proposed to optimize IRS phase shift, namely vector trajectory (VT) method, cross entropy vector trajectory (CE-VT) algorithm, and block coordinate descent vector trajectory (BCD-VT) algorithm.

Position

Can LLMs Really Learn to Translate a Low-Resource Language from One Grammar Book?

no code implementations27 Sep 2024 Seth Aycock, David Stap, Di wu, Christof Monz, Khalil Sima'an

We thus emphasise the importance of task-appropriate data for XLR languages: parallel examples for translation, and grammatical data for linguistic tasks.

Machine Translation Translation

Bitcoin ETF: Opportunities and risk

no code implementations30 Aug 2024 Di wu

The year 2024 witnessed a major development in the cryptocurrency industry with the long-awaited approval of spot Bitcoin exchange-traded funds (ETFs).

Economic Optimal Power Management of Second-Life Battery Energy Storage Systems

no code implementations29 Aug 2024 Amir Farakhor, Di wu, Pingen Chen, Junmin Wang, Yebin Wang, Huazhen Fang

In particular, we capture the degradation costs of the retired battery packs through a weighted average Ah-throughput aging model.

Management

Convolutional Neural Network Compression Based on Low-Rank Decomposition

no code implementations29 Aug 2024 Yaping He, Linhao Jiang, Di wu

Initially, the model undergoes over-parameterization and training, with orthogonal regularization applied to enhance its likelihood of achieving the accuracy of the original model.

Neural Network Compression Tensor Decomposition

The effects of data preprocessing on probability of default model fairness

no code implementations28 Aug 2024 Di wu

In the context of financial credit risk evaluation, the fairness of machine learning models has become a critical concern, especially given the potential for biased predictions that disproportionately affect certain demographic groups.

Fairness

Self-Refined Generative Foundation Models for Wireless Traffic Prediction

no code implementations19 Aug 2024 Chengming Hu, Hao Zhou, Di wu, Xi Chen, Jun Yan, Xue Liu

Following this comprehensive feedback, our proposed TrafficLLM introduces refinement demonstration prompts, enabling the same LLM to further refine its predictions and thereby enhance prediction performance.

Few-Shot Learning In-Context Learning +3

Fairness-Aware Streaming Feature Selection with Causal Graphs

1 code implementation17 Aug 2024 Leizhen Zhang, Lusi Li, Di wu, Sheng Chen, Yi He

The technical challenge of our setting is twofold: 1) streaming feature inputs, such that an informative feature may become obsolete or redundant for prediction if its information has been covered by other similar features that arrived prior to it, and 2) non-associational feature correlation, such that bias may be leaked from those seemingly admissible, non-protected features.

Fairness Feature Correlation +1

Infra-YOLO: Efficient Neural Network Structure with Model Compression for Real-Time Infrared Small Object Detection

no code implementations14 Aug 2024 Zhonglin Chen, Anyu Geng, Jianan Jiang, Jiwu Lu, Di wu

The proposed FFAFPM can enrich semantic information, and enhance the fusion of shallow feature and deep feature, thus false positive results have been significantly reduced.

Efficient Neural Network Model Compression +3

Generative AI as a Service in 6G Edge-Cloud: Generation Task Offloading by In-context Learning

no code implementations5 Aug 2024 Hao Zhou, Chengming Hu, Dun Yuan, Ye Yuan, Di wu, Xue Liu, Zhu Han, Charlie Zhang

In particular, we first introduce the communication system model, i. e., allocating radio resources and calculating link capacity to support generated content transmission, and then we present the LLM inference model to calculate the delay of content generation.

In-Context Learning

Robust Load Prediction of Power Network Clusters Based on Cloud-Model-Improved Transformer

no code implementations30 Jul 2024 Cheng Jiang, Gang Lu, Xue Ma, Di wu

Load data from power network clusters indicates economic development in each area, crucial for predicting regional trends and guiding power enterprise decisions.

Federated Learning based Latent Factorization of Tensors for Privacy-Preserving QoS Prediction

no code implementations29 Jul 2024 Shuai Zhong, Zengtong Tang, Di wu

In applications related to big data and service computing, dynamic connections tend to be encountered, especially the dynamic data of user-perspective quality of service (QoS) in Web services.

Federated Learning Privacy Preserving

Appformer: A Novel Framework for Mobile App Usage Prediction Leveraging Progressive Multi-Modal Data Fusion and Feature Extraction

no code implementations28 Jul 2024 Chuike Sun, Junzhou Chen, Yue Zhao, Hao Han, Ruihai Jing, Guang Tan, Di wu

This article presents Appformer, a novel mobile application prediction framework inspired by the efficiency of Transformer-like architectures in processing sequential data through self-attention mechanisms.

Time Series Analysis Word Embeddings

LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks

1 code implementation19 Jul 2024 Ruokai Yin, Youngeun Kim, Di wu, Priyadarshini Panda

We observe that naively running a dual-sparse SNN on existing spMspM accelerators designed for dual-sparse Artificial Neural Networks (ANNs) exhibits sub-optimal efficiency.

The Factuality Tax of Diversity-Intervened Text-to-Image Generation: Benchmark and Fact-Augmented Intervention

no code implementations29 Jun 2024 Yixin Wan, Di wu, Haoran Wang, Kai-Wei Chang

In this work, we propose DemOgraphic FActualIty Representation (DoFaiR), a benchmark to systematically quantify the trade-off between using diversity interventions and preserving demographic factuality in T2I models.

Diversity Language Modelling +2

MetaKP: On-Demand Keyphrase Generation

1 code implementation28 Jun 2024 Di wu, Xiaoxian Shen, Kai-Wei Chang

Leveraging MetaKP, we design both supervised and unsupervised methods, including a multi-task fine-tuning approach and a self-consistency prompting method with large language models.

Event Detection Keyphrase Generation

Synchronous Faithfulness Monitoring for Trustworthy Retrieval-Augmented Generation

1 code implementation19 Jun 2024 Di wu, Jia-Chen Gu, Fan Yin, Nanyun Peng, Kai-Wei Chang

Retrieval-augmented language models (RALMs) have shown strong performance and wide applicability in knowledge-intensive tasks.

Retrieval Uncertainty Quantification

Towards Self-Supervised FG-SBIR with Unified Sample Feature Alignment and Multi-Scale Token Recycling

no code implementations17 Jun 2024 Jianan Jiang, Di wu, Zhilin Jiang, Weiren Yu

Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) aims to minimize the distance between sketches and corresponding images in the embedding space.

Sketch-Based Image Retrieval

A Survey of Deep Learning Based Radar and Vision Fusion for 3D Object Detection in Autonomous Driving

no code implementations2 Jun 2024 Di wu, Feng Yang, Benlian Xu, Pan Liao, Bo Liu

This paper focuses on a comprehensive survey of radar-vision (RV) fusion based on deep learning methods for 3D object detection in autonomous driving.

3D Object Detection Autonomous Driving +1

FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning

1 code implementation2 Jun 2024 Yuwei Fu, Haichao Zhang, Di wu, Wei Xu, Benoit Boulet

In this work, we investigate how to leverage pre-trained visual-language models (VLM) for online Reinforcement Learning (RL).

reinforcement-learning Reinforcement Learning (RL)

MonoDETRNext: Next-generation Accurate and Efficient Monocular 3D Object Detection Method

no code implementations24 May 2024 Pan Liao, Feng Yang, Di wu, Liu Bo

We posit that MonoDETRNext establishes a new benchmark in monocular 3D object detection and opens avenues for future research.

Computational Efficiency Depth Estimation +3

CityGPT: Towards Urban IoT Learning, Analysis and Interaction with Multi-Agent System

no code implementations23 May 2024 Qinghua Guan, Jinhui Ouyang, Di wu, Weiren Yu

Finally, the spatiotemporal fusion agent visualizes the system's analysis results by receiving analysis results from data analysis agents and invoking sub-visualization agents, and can provide corresponding textual descriptions based on user demands.

Language Modelling Large Language Model

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling

no code implementations13 May 2024 Siyuan Li, Zedong Wang, Zicheng Liu, Di wu, Cheng Tan, Jiangbin Zheng, Yufei Huang, Stan Z. Li

In this paper, we introduce VQDNA, a general-purpose framework that renovates genome tokenization from the perspective of genome vocabulary learning.

Quantization

TrafficGPT: Towards Multi-Scale Traffic Analysis and Generation with Spatial-Temporal Agent Framework

no code implementations8 May 2024 Jinhui Ouyang, Yijie Zhu, Xiang Yuan, Di wu

The precise prediction of multi-scale traffic is a ubiquitous challenge in the urbanization process for car owners, road administrators, and governments.

Traffic Prediction

Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling

no code implementations27 Apr 2024 Di wu, Shicai Fan, Xue Zhou, Li Yu, Yuzhong Deng, Jianxiao Zou, Baihong Lin

In MDPS, the problem of normal image reconstruction is mathematically modeled as multiple diffusion posterior sampling for normal images based on the devised masked noisy observation model and the diffusion-based normal image prior under Bayesian framework.

Image Reconstruction Unsupervised Anomaly Detection

FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning

no code implementations22 Apr 2024 Yinlin Zhu, Xunkai Li, Zhengyu Wu, Di wu, Miao Hu, Rong-Hua Li

Subgraph federated learning (subgraph-FL) is a new distributed paradigm that facilitates the collaborative training of graph neural networks (GNNs) by multi-client subgraphs.

Data-free Knowledge Distillation Federated Learning +1

An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehicles

no code implementations18 Apr 2024 Jilan Samiuddin, Benoit Boulet, Di wu

Among these modules, the trajectory planner plays a pivotal role in the safety of the vehicle and the comfort of its passengers.

Autonomous Driving

ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching

no code implementations26 Mar 2024 Youpeng Zhao, Di wu, Jun Wang

In a single GPU-CPU system, we demonstrate that under varying workloads, ALISA improves the throughput of baseline systems such as FlexGen and vLLM by up to 3X and 1. 9X, respectively.

Language Modelling Large Language Model +1

Repoformer: Selective Retrieval for Repository-Level Code Completion

no code implementations15 Mar 2024 Di wu, Wasi Uddin Ahmad, Dejiao Zhang, Murali Krishna Ramanathan, Xiaofei Ma

Recent advances in retrieval-augmented generation (RAG) have initiated a new era in repository-level code completion.

Code Completion RAG +2

BRIEDGE: EEG-Adaptive Edge AI for Multi-Brain to Multi-Robot Interaction

no code implementations14 Mar 2024 Jinhui Ouyang, Mingzhu Wu, Xinglin Li, Hanhui Deng, Di wu

To better extract the joint features of heterogeneous EEG data as well as enhance classification accuracy, BRIEDGE introduces an informer-based ProbSparse self-attention mechanism.

EEG Model Compression +1

Prototyping and Experimental Results for Environment-Aware Millimeter Wave Beam Alignment via Channel Knowledge Map

no code implementations13 Mar 2024 Zhuoyin Dai, Di wu, Zhenjun Dong, Kun Li, Dingyang Ding, Sihan Wang, Yong Zeng

In this paper, to alleviate the large training overhead in millimeter wave (mmWave) beam alignment, an environment-aware and training-free beam alignment prototype is established based on a typical CKM, termed beam index map (BIM).

HAIFIT: Human-to-AI Fashion Image Translation

1 code implementation13 Mar 2024 Jianan Jiang, Xinglin Li, Weiren Yu, Di wu

In the realm of fashion design, sketches serve as the canvas for expressing an artist's distinctive drawing style and creative vision, capturing intricate details like stroke variations and texture nuances.

Image Generation Translation

Qubit-Wise Architecture Search Method for Variational Quantum Circuits

no code implementations7 Mar 2024 Jialin Chen, Zhiqiang Cai, Ke Xu, Di wu, Wei Cao

Considering the noise level limit, one crucial aspect for quantum machine learning is to design a high-performing variational quantum circuit architecture with small number of quantum gates.

Evolutionary Algorithms Neural Architecture Search +1

NoteLLM: A Retrievable Large Language Model for Note Recommendation

no code implementations4 Mar 2024 Chao Zhang, Shiwei Wu, Haoxin Zhang, Tong Xu, Yan Gao, Yao Hu, Di wu, Enhong Chen

Indeed, learning to generate hashtags/categories can potentially enhance note embeddings, both of which compress key note information into limited content.

Contrastive Learning Language Modelling +1

Meta-Task Prompting Elicits Embeddings from Large Language Models

1 code implementation28 Feb 2024 Yibin Lei, Di wu, Tianyi Zhou, Tao Shen, Yu Cao, Chongyang Tao, Andrew Yates

We introduce a new unsupervised text embedding method, Meta-Task Prompting with Explicit One-Word Limitation (MetaEOL), for generating high-quality sentence embeddings from Large Language Models (LLMs) without the need for model fine-tuning.

Semantic Textual Similarity Sentence +2

G4G:A Generic Framework for High Fidelity Talking Face Generation with Fine-grained Intra-modal Alignment

no code implementations28 Feb 2024 Juan Zhang, Jiahao Chen, Cheng Wang, Zhiwang Yu, Tangquan Qi, Di wu

Despite numerous completed studies, achieving high fidelity talking face generation with highly synchronized lip movements corresponding to arbitrary audio remains a significant challenge in the field.

Talking Face Generation

On Leveraging Encoder-only Pre-trained Language Models for Effective Keyphrase Generation

1 code implementation21 Feb 2024 Di wu, Wasi Uddin Ahmad, Kai-Wei Chang

This study addresses the application of encoder-only Pre-trained Language Models (PLMs) in keyphrase generation (KPG) amidst the broader availability of domain-tailored encoder-only models compared to encoder-decoder models.

Decoder Keyphrase Generation

Switch EMA: A Free Lunch for Better Flatness and Sharpness

3 code implementations14 Feb 2024 Siyuan Li, Zicheng Liu, Juanxi Tian, Ge Wang, Zedong Wang, Weiyang Jin, Di wu, Cheng Tan, Tao Lin, Yang Liu, Baigui Sun, Stan Z. Li

Exponential Moving Average (EMA) is a widely used weight averaging (WA) regularization to learn flat optima for better generalizations without extra cost in deep neural network (DNN) optimization.

Attribute Image Classification +7

Graph Attention-based Reinforcement Learning for Trajectory Design and Resource Assignment in Multi-UAV Assisted Communication

no code implementations31 Jan 2024 Zikai Feng, Di wu, Mengxing Huang, Chau Yuen

In this paper, a novel graph-attention multi-agent trust region (GA-MATR) reinforcement learning framework is proposed to solve the multi-UAV assisted communication problem.

Decision Making Graph Attention +2

Analysis of Knowledge Tracing performance on synthesised student data

no code implementations30 Jan 2024 Panagiotis Pagonis, Kai Hartung, Di wu, Munir Georges, Sören Gröttrup

Knowledge Tracing (KT) aims to predict the future performance of students by tracking the development of their knowledge states.

Diversity Knowledge Tracing

A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research

no code implementations26 Jan 2024 Sicong Cao, Xiaobing Sun, Ratnadira Widyasari, David Lo, Xiaoxue Wu, Lili Bo, Jiale Zhang, Bin Li, Wei Liu, Di wu, Yixin Chen

The remarkable achievements of Artificial Intelligence (AI) algorithms, particularly in Machine Learning (ML) and Deep Learning (DL), have fueled their extensive deployment across multiple sectors, including Software Engineering (SE).

Decision Making Systematic Literature Review +1

How Far Can 100 Samples Go? Unlocking Overall Zero-Shot Multilingual Translation via Tiny Multi-Parallel Data

1 code implementation22 Jan 2024 Di wu, Shaomu Tan, Yan Meng, David Stap, Christof Monz

Zero-shot translation aims to translate between language pairs not seen during training in Multilingual Machine Translation (MMT) and is largely considered an open problem.

Machine Translation Translation

Hallucination Detection and Hallucination Mitigation: An Investigation

no code implementations16 Jan 2024 Junliang Luo, Tianyu Li, Di wu, Michael Jenkin, Steve Liu, Gregory Dudek

Large language models (LLMs), including ChatGPT, Bard, and Llama, have achieved remarkable successes over the last two years in a range of different applications.

Hallucination

On the Selection of Intermediate Length Representative Periods for Capacity Expansion

no code implementations5 Jan 2024 Osten Anderson, Nanpeng Yu, Konstantinos Oikonomou, Di wu

To this end, we propose a novel method for selecting representative periods of any length.

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond

1 code implementation31 Dec 2023 Siyuan Li, Luyuan Zhang, Zedong Wang, Di wu, Lirong Wu, Zicheng Liu, Jun Xia, Cheng Tan, Yang Liu, Baigui Sun, Stan Z. Li

As the deep learning revolution marches on, self-supervised learning has garnered increasing attention in recent years thanks to its remarkable representation learning ability and the low dependence on labeled data.

Representation Learning Self-Supervised Learning +1

A Joint Multi-Gradient Algorithm for Demosaicing Bayer Images

no code implementations International Conference on Communication, Image and Signal Processing (CCISP) 2023 Di wu, Zhihui Xin, Chao Zhang

Experiments show that the algorithm in this paper has better recovery in image edges as well as texture complex regions with higher PSNR and SSIM values and better subjective visual perception compared to the traditional gradient algorithms such as BI, Cok, Hibbard, Laroche, Hamiton, while the algorithm involves only the add-subtract and shift operations, which is suitable to be implemented on the hardware platform.

Demosaicking SSIM

Neural Network Approximation for Pessimistic Offline Reinforcement Learning

no code implementations19 Dec 2023 Di wu, Yuling Jiao, Li Shen, Haizhao Yang, Xiliang Lu

In this paper, we establish a non-asymptotic estimation error of pessimistic offline RL using general neural network approximation with $\mathcal{C}$-mixing data regarding the structure of networks, the dimension of datasets, and the concentrability of data coverage, under mild assumptions.

Offline RL reinforcement-learning +2

Traffic Signal Control Using Lightweight Transformers: An Offline-to-Online RL Approach

1 code implementation12 Dec 2023 Xingshuai Huang, Di wu, Benoit Boulet

In this work, we propose DTLight, a simple yet powerful lightweight Decision Transformer-based TSC method that can learn policy from easily accessible offline datasets.

Knowledge Distillation Offline RL +2

Anomaly Detection for Scalable Task Grouping in Reinforcement Learning-based RAN Optimization

no code implementations6 Dec 2023 Jimmy Li, Igor Kozlov, Di wu, Xue Liu, Gregory Dudek

This coincides with a rapid increase in the number of cell sites worldwide, driven largely by dramatic growth in cellular network traffic.

Anomaly Detection

Attend Who is Weak: Enhancing Graph Condensation via Cross-Free Adversarial Training

no code implementations27 Nov 2023 Xinglin Li, Kun Wang, Hanhui Deng, Yuxuan Liang, Di wu

We seminally propose the concept of Shock Absorber (a type of perturbation) that enhances the robustness and stability of the original graphs against changes in an adversarial training fashion.

Node Classification

Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive Tasks

1 code implementation1 Nov 2023 Po-Nien Kung, Fan Yin, Di wu, Kai-Wei Chang, Nanyun Peng

Instruction tuning (IT) achieves impressive zero-shot generalization results by training large language models (LLMs) on a massive amount of diverse tasks with instructions.

Informativeness Out-of-Distribution Generalization +1

Scalable Optimal Power Management for Large-Scale Battery Energy Storage Systems

no code implementations25 Oct 2023 Amir Farakhor, Di wu, Yebin Wang, Huazhen Fang

Since the number of clusters is much fewer than the number of cells, the proposed approach significantly reduces the computational costs, allowing optimal power management to scale up to large-scale BESS.

Management

Online Two-stage Thermal History Prediction Method for Metal Additive Manufacturing of Thin Walls

no code implementations24 Oct 2023 Yifan Tang, M. Rahmani Dehaghani, Pouyan Sajadi, Shahriar Bakrani Balani, Akshay Dhalpe, Suraj Panicker, Di wu, Eric Coatanea, G. Gary Wang

With measured/predicted temperature profiles of several points on the same layer, the second stage proposes a reduced order model (ROM) (intra-layer prediction model) to decompose and construct the temperature profiles of all points on the same layer, which could be used to build the temperature field of the entire layer.

ARC Computational Efficiency

Enhancing Building Energy Efficiency through Advanced Sizing and Dispatch Methods for Energy Storage

no code implementations19 Oct 2023 Min Gyung Yu, Xu Ma, Bowen Huang, Karthik Devaprasad, Fredericka Brown, Di wu

The solution is determined considering both capital costs in optimal sizing and operational benefits in optimal dispatch.

Decision Making

UvA-MT's Participation in the WMT23 General Translation Shared Task

no code implementations15 Oct 2023 Di wu, Shaomu Tan, David Stap, Ali Araabi, Christof Monz

This paper describes the UvA-MT's submission to the WMT 2023 shared task on general machine translation.

Machine Translation Translation

Adaptive Dynamic Programming for Energy-Efficient Base Station Cell Switching

no code implementations5 Oct 2023 Junliang Luo, Yi Tian Xu, Di wu, Michael Jenkin, Xue Liu, Gregory Dudek

In this work, we propose an approximate dynamic programming (ADP)-based method coupled with online optimization to switch on/off the cells of base stations to reduce network power consumption while maintaining adequate Quality of Service (QoS) metrics.

A Read Margin Enhancement Circuit with Dynamic Bias Optimization for MRAM

no code implementations18 Sep 2023 Renhe Chen, Albert Lee, ZiRui Wang, Di wu, Xufeng Kou

This brief introduces a read bias circuit to improve readout yield of magnetic random access memories (MRAMs).

Virtual histological staining of unlabeled autopsy tissue

no code implementations2 Aug 2023 Yuzhu Li, Nir Pillar, Jingxi Li, Tairan Liu, Di wu, Songyu Sun, Guangdong Ma, Kevin De Haan, Luzhe Huang, Sepehr Hamidi, Anatoly Urisman, Tal Keidar Haran, William Dean Wallace, Jonathan E. Zuckerman, Aydogan Ozcan

Histological examination is a crucial step in an autopsy; however, the traditional histochemical staining of post-mortem samples faces multiple challenges, including the inferior staining quality due to autolysis caused by delayed fixation of cadaver tissue, as well as the resource-intensive nature of chemical staining procedures covering large tissue areas, which demand substantial labor, cost, and time.

Image Registration

Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes

1 code implementation ICCV 2023 Di wu, Pengfei Chen, Xuehui Yu, Guorong Li, Zhenjun Han, Jianbin Jiao

Object detection via inaccurate bounding boxes supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low annotation quality (\eg tiny objects).

Multiple Instance Learning Object +2

Active learning of effective Hamiltonian for super-large-scale atomic structures

no code implementations18 Jul 2023 Xingyue Ma, Hongying Chen, Ri He, Zhanbo Yu, Sergei Prokhorenko, Zheng Wen, Zhicheng Zhong, Jorge Iñiguez, L. Bellaiche, Di wu, Yurong Yang

The first-principles-based effective Hamiltonian scheme provides one of the most accurate modeling technique for large-scale structures, especially for ferroelectrics.

Active Learning

CeBed: A Benchmark for Deep Data-Driven OFDM Channel Estimation

1 code implementation23 Jun 2023 Amal Feriani, Di wu, Steve Liu, Greg Dudek

This work offers a comprehensive and unified framework to help researchers evaluate and design data-driven channel estimation algorithms.

Experimental Design

An Error Correction Mid-term Electricity Load Forecasting Model Based on Seasonal Decomposition

no code implementations19 Jun 2023 Liping Zhang, Di wu, Xin Luo

Then, based on the idea of stacking ensemble, long short-term memory is employed as an error correction module to forecast the components separately, and the forecast results are treated as new features to be fed into extreme gradient boosting for the second-step forecasting.

Feature Engineering Load Forecasting +2

Asymptotic Performance Analysis of Large-Scale Active IRS-Aided Wireless Network

no code implementations31 May 2023 Yan Wang, Feng Shu, Zhihong Zhuang, Rongen Dong, Qi Zhang, Di wu, Liang Yang, Jiangzhou Wang

Numerical simulation results show that a 3-bit discrete phase shifter is required to achieve a trivial performance loss for a large-scale active IRS.

Quantization

Lightweight Learner for Shared Knowledge Lifelong Learning

1 code implementation24 May 2023 Yunhao Ge, Yuecheng Li, Di wu, Ao Xu, Adam M. Jones, Amanda Sofie Rios, Iordanis Fostiropoulos, Shixian Wen, Po-Hsuan Huang, Zachary William Murdock, Gozde Sahin, Shuo Ni, Kiran Lekkala, Sumedh Anand Sontakke, Laurent Itti

We propose a new Shared Knowledge Lifelong Learning (SKILL) challenge, which deploys a decentralized population of LL agents that each sequentially learn different tasks, with all agents operating independently and in parallel.

Image Classification

A new sulfur bioconversion process development for energy- and space-efficient secondary wastewater treatment

no code implementations22 May 2023 Chu-Kuan Jiang, Yang-Fan Deng, Hongxiao Guo, Guang-Hao Chen, Di wu

Typical pretreated wastewater was synthesized with chemical oxygen demand of 110 mg/L, sulfate of 50 mg S/L, and varying dissolved oxygen (DO) and was fed into a moving-bed biofilm reactor (MBBR).

ZeroPrompt: Streaming Acoustic Encoders are Zero-Shot Masked LMs

no code implementations18 May 2023 Xingchen Song, Di wu, BinBin Zhang, Zhendong Peng, Bo Dang, Fuping Pan, Zhiyong Wu

In this paper, we present ZeroPrompt (Figure 1-(a)) and the corresponding Prompt-and-Refine strategy (Figure 3), two simple but effective \textbf{training-free} methods to decrease the Token Display Time (TDT) of streaming ASR models \textbf{without any accuracy loss}.

FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment

1 code implementation10 May 2023 Jiahao Liu, Jiang Wu, Jinyu Chen, Miao Hu, Yipeng Zhou, Di wu

In this paper, we propose a new PFL algorithm called \emph{FedDWA (Federated Learning with Dynamic Weight Adjustment)} to address the above problem, which leverages the parameter server (PS) to compute personalized aggregation weights based on collected models from clients.

Personalized Federated Learning

BARA: Efficient Incentive Mechanism with Online Reward Budget Allocation in Cross-Silo Federated Learning

no code implementations9 May 2023 Yunchao Yang, Yipeng Zhou, Miao Hu, Di wu, Quan Z. Sheng

The challenge of this problem lies in the opaque feedback between reward budget allocation and model utility improvement of FL, making the optimal reward budget allocation complicated.

Bayesian Optimization Federated Learning

KPEval: Towards Fine-Grained Semantic-Based Keyphrase Evaluation

1 code implementation27 Mar 2023 Di wu, Da Yin, Kai-Wei Chang

Despite the significant advancements in keyphrase extraction and keyphrase generation methods, the predominant approach for evaluation mainly relies on exact matching with human references.

Diversity Keyphrase Extraction +1

Edge-Based Video Analytics: A Survey

no code implementations25 Mar 2023 Miao Hu, Zhenxiao Luo, Amirmohammad Pasdar, Young Choon Lee, Yipeng Zhou, Di wu

Edge computing has been getting a momentum with ever-increasing data at the edge of the network.

Cloud Computing Edge-computing +2

From Wide to Deep: Dimension Lifting Network for Parameter-efficient Knowledge Graph Embedding

no code implementations22 Mar 2023 Borui Cai, Yong Xiang, Longxiang Gao, Di wu, He Zhang, Jiong Jin, Tom Luan

To seek a simple strategy to improve the parameter efficiency of conventional KGE models, we take inspiration from that deeper neural networks require exponentially fewer parameters to achieve expressiveness comparable to wider networks for compositional structures.

Knowledge Distillation Knowledge Graph Embedding +2

Communication Load Balancing via Efficient Inverse Reinforcement Learning

no code implementations22 Mar 2023 Abhisek Konar, Di wu, Yi Tian Xu, Seowoo Jang, Steve Liu, Gregory Dudek

Engineering this reward function is challenging, because it involves the need for expert knowledge and there lacks a general consensus on the form of an optimal reward function.

reinforcement-learning Reinforcement Learning +1

Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios

no code implementations22 Mar 2023 Yi Tian Xu, Jimmy Li, Di wu, Michael Jenkin, Seowoo Jang, Xue Liu, Gregory Dudek

When deploying to an unknown traffic scenario, we select a policy from the policy bank based on the similarity between the previous-day traffic of the current scenario and the traffic observed during training.

Reinforcement Learning (RL)

Multi-agent Attention Actor-Critic Algorithm for Load Balancing in Cellular Networks

no code implementations14 Mar 2023 Jikun Kang, Di wu, Ju Wang, Ekram Hossain, Xue Liu, Gregory Dudek

In cellular networks, User Equipment (UE) handoff from one Base Station (BS) to another, giving rise to the load balancing problem among the BSs.

Online Sparse Streaming Feature Selection Using Adapted Classification

no code implementations25 Feb 2023 Ruiyang Xu, Di wu, Xin Luo

Traditional feature selections need to know the feature space before learning, and online streaming feature selection (OSFS) is proposed to process streaming features on the fly.

Classification Feature Correlation +1

Adaptive Aggregation for Safety-Critical Control

no code implementations7 Feb 2023 Huiliang Zhang, Di wu, Benoit Boulet

Safety has been recognized as the central obstacle to preventing the use of reinforcement learning (RL) for real-world applications.

reinforcement-learning Reinforcement Learning +3

Self-Supervised Transformer Architecture for Change Detection in Radio Access Networks

no code implementations3 Feb 2023 Igor Kozlov, Dmitriy Rivkin, Wei-Di Chang, Di wu, Xue Liu, Gregory Dudek

Such networks undergo frequent and often heterogeneous changes caused by network operators, who are seeking to tune their system parameters for optimal performance.

Change Detection Self-Supervised Learning

A Novel Modular, Reconfigurable Battery Energy Storage System: Design, Control, and Experimentation

no code implementations12 Jan 2023 Amir Farakhor, Di wu, Yebin Wang, Huazhen Fang

An optimal power management approach is developed to extensively exploit the merits of the proposed design.

Management

Multi-Metric AutoRec for High Dimensional and Sparse User Behavior Data Prediction

no code implementations20 Dec 2022 Cheng Liang, Teng Huang, Yi He, Song Deng, Di wu, Xin Luo

The idea of the proposed MMA is mainly two-fold: 1) apply different $L_p$-norm on loss function and regularization to form different variant models in different metric spaces, and 2) aggregate these variant models.

Diversity Recommendation Systems

Pre-trained Language Models for Keyphrase Generation: A Thorough Empirical Study

1 code implementation20 Dec 2022 Di wu, Wasi Uddin Ahmad, Kai-Wei Chang

However, there lacks a systematic study of how the two types of approaches compare and how different design choices can affect the performance of PLM-based models.

Decoder Keyphrase Extraction +1

Original or Translated? On the Use of Parallel Data for Translation Quality Estimation

no code implementations20 Dec 2022 Baopu Qiu, Liang Ding, Di wu, Lin Shang, Yibing Zhan, DaCheng Tao

Machine Translation Quality Estimation (QE) is the task of evaluating translation output in the absence of human-written references.

Data Augmentation Machine Translation +2

Design Considerations of a Coordinative Demand Charge Mitigation Strategy

no code implementations16 Dec 2022 Rongxing Hu, Kai Ye, Hyeonjin Kim, Hanpyo Lee, Ning Lu, Di wu, PJ Rehm

This paper presents a coordinative demand charge mitigation (DCM) strategy for reducing electricity consumption during system peak periods.

energy management Management

Relightable Neural Human Assets from Multi-view Gradient Illuminations

no code implementations CVPR 2023 Taotao Zhou, Kai He, Di wu, Teng Xu, Qixuan Zhang, Kuixiang Shao, Wenzheng Chen, Lan Xu, Jingyi Yu

UltraStage will be publicly available to the community to stimulate significant future developments in various human modeling and rendering tasks.

Image Relighting Novel View Synthesis

A Modified Sequence-to-point HVAC Load Disaggregation Algorithm

no code implementations9 Dec 2022 Kai Ye, Hyeonjin Kim, Yi Hu, Ning Lu, Di wu, PJ Rehm

This paper presents a modified sequence-to-point (S2P) algorithm for disaggregating the heat, ventilation, and air conditioning (HVAC) load from the total building electricity consumption.

Dual Class-Aware Contrastive Federated Semi-Supervised Learning

no code implementations16 Nov 2022 Qi Guo, Yong Qi, Saiyu Qi, Di wu

To our knowledge, we are the first to present an FSSL method that utilizes only 10\% labeled clients, while still achieving superior performance compared to standard federated supervised learning, which uses all clients with labeled data.

MogaNet: Multi-order Gated Aggregation Network

7 code implementations7 Nov 2022 Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di wu, ZhiYuan Chen, Jiangbin Zheng, Stan Z. Li

Notably, MogaNet hits 80. 0\% and 87. 8\% accuracy with 5. 2M and 181M parameters on ImageNet-1K, outperforming ParC-Net and ConvNeXt-L, while saving 59\% FLOPs and 17M parameters, respectively.

3D Human Pose Estimation Image Classification +6

An Iterative Bidirectional Gradient Boosting Approach for CVR Baseline Estimation

no code implementations7 Nov 2022 Han Pyo Lee, Yiyan Li, Lidong Song, Di wu, Ning Lu

In contrast to many existing methods, we treat CVR baseline estimation as a missing data retrieval problem.

TrimTail: Low-Latency Streaming ASR with Simple but Effective Spectrogram-Level Length Penalty

1 code implementation1 Nov 2022 Xingchen Song, Di wu, Zhiyong Wu, BinBin Zhang, Yuekai Zhang, Zhendong Peng, Wenpeng Li, Fuping Pan, Changbao Zhu

In this paper, we present TrimTail, a simple but effective emission regularization method to improve the latency of streaming ASR models.

Deep Koopman Learning of Nonlinear Time-Varying Systems

no code implementations12 Oct 2022 Wenjian Hao, Bowen Huang, Wei Pan, Di wu, Shaoshuai Mou

This paper presents a data-driven approach to approximate the dynamics of a nonlinear time-varying system (NTVS) by a linear time-varying system (LTVS), which is resulted from the Koopman operator and deep neural networks.

Computational Efficiency

Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond

no code implementations3 Oct 2022 Di wu, Jie Yang, Mohamad Sawan

In this survey, we assess the eligibility of more than fifty published peer-reviewed representative transfer learning approaches for EMG applications.

Electromyography (EMG) Survey +1

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

no code implementations19 Sep 2022 Hyeonjin Kim, Kai Ye, Han Pyo Lee, Rongxing Hu, Ning Lu, Di wu, PJ Rehm

The residual load profiles are processed using ICA for HVAC load extraction.

OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning

1 code implementation11 Sep 2022 Siyuan Li, Zedong Wang, Zicheng Liu, Juanxi Tian, Di wu, Cheng Tan, Weiyang Jin, Stan Z. Li

Mixup augmentation has emerged as a widely used technique for improving the generalization ability of deep neural networks (DNNs).

Benchmarking Classification +3

DPAUC: Differentially Private AUC Computation in Federated Learning

1 code implementation25 Aug 2022 Jiankai Sun, Xin Yang, Yuanshun Yao, Junyuan Xie, Di wu, Chong Wang

Federated learning (FL) has gained significant attention recently as a privacy-enhancing tool to jointly train a machine learning model by multiple participants.

Federated Learning

FedMCSA: Personalized Federated Learning via Model Components Self-Attention

no code implementations23 Aug 2022 Qi Guo, Yong Qi, Saiyu Qi, Di wu, Qian Li

Federated learning (FL) facilitates multiple clients to jointly train a machine learning model without sharing their private data.

Personalized Federated Learning

A Latent Feature Analysis-based Approach for Spatio-Temporal Traffic Data Recovery

no code implementations16 Aug 2022 Yuting Ding, Di wu

In the past decade, scholars have done many research on the recovery of missing traffic data, however how to make full use of spatio-temporal traffic patterns to improve the recovery performance is still an open problem.

Matrix Completion

Optimal Measurement of Drone Swarm in RSS-based Passive Localization with Region Constraints

no code implementations2 Aug 2022 Xin Cheng, Feng Shu, YiFan Li, Zhihong Zhuang, Di wu, Jiangzhou Wang

In this paper, optimal geometrical configurations of UAVs in received signal strength (RSS)-based localization under region constraints are investigated.

An Online Sparse Streaming Feature Selection Algorithm

no code implementations2 Aug 2022 Feilong Chen, Di wu, Jie Yang, Yi He

In many real applications such as intelligent healthcare platform, streaming feature always has some missing data, which raises a crucial challenge in conducting OSFS, i. e., how to establish the uncertain relationship between sparse streaming features and labels.

feature selection

Energy Storage State-of-Charge Market Model

no code implementations14 Jul 2022 Ningkun Zheng, Xin Qin, Di wu, Gabe Murtaugh, Bolun Xu

Combined with an optimal bidding design algorithm using dynamic programming, our paper shows that the SoC segment market model provides more accurate representations of the opportunity costs of energy storage compared to existing power-based bidding models.

DLME: Deep Local-flatness Manifold Embedding

2 code implementations7 Jul 2022 Zelin Zang, Siyuan Li, Di wu, Ge Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li

To overcome the underconstrained embedding problem, we design a loss and theoretically demonstrate that it leads to a more suitable embedding based on the local flatness.

Contrastive Learning Data Augmentation +1

Reinforcement Learning Based Dynamic Model Combination for Time Series Forecasting

no code implementations AAAI Conference on Artificial Intelligence 2022 Yuwei Fu, Di wu, Benoit Boulet

To deal with this challenge, we propose a reinforcement learning (RL) based model combination (RLMC) framework for determining model weights in an ensemble for time series forecasting tasks.

Decision Making Ensemble Learning +7

HIFI-Net: A Novel Network for Enhancement to Underwater Images

no code implementations6 Jun 2022 Jiajia Zhou, Junbin Zhuang, Yan Zheng, Di wu

As this network make "Haar Images into Fusion Images", it is called HIFI-Net.

Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN

3 code implementations27 May 2022 Siyuan Li, Di wu, Fang Wu, Zelin Zang, Stan. Z. Li

We then propose an Architecture-Agnostic Masked Image Modeling framework (A$^2$MIM), which is compatible with both Transformers and CNNs in a unified way.

Instance Segmentation Object Detection +3

MALICE: Manipulation Attacks on Learned Image ComprEssion

no code implementations26 May 2022 Kang Liu, Di wu, Yiru Wang, Dan Feng, Benjamin Tan, Siddharth Garg

To characterize the robustness of state-of-the-art learned image compression, we mount white-box and black-box attacks.

Image Compression Image Reconstruction

Differentially Private AUC Computation in Vertical Federated Learning

no code implementations24 May 2022 Jiankai Sun, Xin Yang, Yuanshun Yao, Junyuan Xie, Di wu, Chong Wang

In this work, we propose two evaluation algorithms that can more accurately compute the widely used AUC (area under curve) metric when using label DP in vFL.

Vertical Federated Learning

Time Series Anomaly Detection via Reinforcement Learning-Based Model Selection

1 code implementation19 May 2022 Jiuqi Elise Zhang, Di wu, Benoit Boulet

Time series anomaly detection has been recognized as of critical importance for the reliable and efficient operation of real-world systems.

Anomaly Detection Model Selection +5

An Early Fault Detection Method of Rotating Machines Based on Multiple Feature Fusion with Stacking Architecture

no code implementations1 May 2022 Wenbin Song, Di wu, Weiming Shen, Benoit Boulet

One of the key points of EFD is developing a generic model to extract robust and discriminative features from different equipment for early fault detection.

Denoising Fault Detection

Meta-Learning Based Early Fault Detection for Rolling Bearings via Few-Shot Anomaly Detection

no code implementations27 Apr 2022 Wenbin Song, Di wu, Weiming Shen, Benoit Boulet

To address this problem, many transfer learning based EFD methods utilize historical data to learn transferable domain knowledge and conduct early fault detection on new target bearings.

Anomaly Detection Fault Detection +3

Neuro-BERT: Rethinking Masked Autoencoding for Self-supervised Neurological Pretraining

1 code implementation20 Apr 2022 Di wu, Siyuan Li, Jie Yang, Mohamad Sawan

To address the appetite for data in deep learning, we present Neuro-BERT, a self-supervised pre-training framework of neurological signals based on masked autoencoding in the Fourier domain.

EEG Electromyography (EMG) +2

A Multi-Metric Latent Factor Model for Analyzing High-Dimensional and Sparse data

no code implementations16 Apr 2022 Di wu, Peng Zhang, Yi He, Xin Luo

High-dimensional and sparse (HiDS) matrices are omnipresent in a variety of big data-related applications.

Representation Learning

Graph-incorporated Latent Factor Analysis for High-dimensional and Sparse Matrices

no code implementations16 Apr 2022 Di wu, Yi He, Xin Luo

A High-dimensional and sparse (HiDS) matrix is frequently encountered in a big data-related application like an e-commerce system or a social network services system.

Representation Learning Vocal Bursts Intensity Prediction

A Differential Evolution-Enhanced Latent Factor Analysis Model for High-dimensional and Sparse Data

no code implementations2 Apr 2022 Jia Chen, Di wu, Xin Luo

High-dimensional and sparse (HiDS) matrices are frequently adopted to describe the complex relationships in various big data-related systems and applications.

Position

WeNet 2.0: More Productive End-to-End Speech Recognition Toolkit

3 code implementations29 Mar 2022 BinBin Zhang, Di wu, Zhendong Peng, Xingchen Song, Zhuoyuan Yao, Hang Lv, Lei Xie, Chao Yang, Fuping Pan, Jianwei Niu

Recently, we made available WeNet, a production-oriented end-to-end speech recognition toolkit, which introduces a unified two-pass (U2) framework and a built-in runtime to address the streaming and non-streaming decoding modes in a single model.

Decoder Language Modelling +2

Predicting Peak Day and Peak Hour of Electricity Demand with Ensemble Machine Learning

no code implementations25 Mar 2022 Tao Fu, Huifen Zhou, Xu Ma, Z. Jason Hou, Di wu

In this study, we develop a supervised machine learning approach to generate 1) the probability of the next operation day containing the peak hour of the month and 2) the probability of an hour to be the peak hour of the day.

BIG-bench Machine Learning Decision Making

Object Localization under Single Coarse Point Supervision

2 code implementations CVPR 2022 Xuehui Yu, Pengfei Chen, Di wu, Najmul Hassan, Guorong Li, Junchi Yan, Humphrey Shi, Qixiang Ye, Zhenjun Han

In this study, we propose a POL method using coarse point annotations, relaxing the supervision signals from accurate key points to freely spotted points.

Multiple Instance Learning Object +1

Representation Learning for Resource-Constrained Keyphrase Generation

1 code implementation15 Mar 2022 Di wu, Wasi Uddin Ahmad, Sunipa Dev, Kai-Wei Chang

State-of-the-art keyphrase generation methods generally depend on large annotated datasets, limiting their performance in domains with limited annotated data.

Denoising Domain Adaptation +4

Impression Allocation and Policy Search in Display Advertising

no code implementations11 Mar 2022 Di wu, Cheng Chen, Xiujun Chen, Junwei Pan, Xun Yang, Qing Tan, Jian Xu, Kuang-Chih Lee

In order to address the unstable traffic pattern challenge and achieve the optimal overall outcome, we propose a multi-agent reinforcement learning method to adjust the bids from each guaranteed contract, which is simple, converging efficiently and scalable.

Multi-agent Reinforcement Learning

Bridging the Gap Between Patient-specific and Patient-independent Seizure Prediction via Knowledge Distillation

no code implementations25 Feb 2022 Di wu, Jie Yang, Mohamad Sawan

The proposed training scheme significantly improves the performance of patient-specific seizure predictors and bridges the gap between patient-specific and patient-independent predictors.

Knowledge Distillation Seizure prediction

Learning to Simulate Unseen Physical Systems with Graph Neural Networks

no code implementations NeurIPS Workshop AI4Scien 2021 Ce Yang, Weihao Gao, Di wu, Chong Wang

Simulation of the dynamics of physical systems is essential to the development of both science and engineering.

Gap Minimization for Knowledge Sharing and Transfer

no code implementations26 Jan 2022 Boyu Wang, Jorge Mendez, Changjian Shui, Fan Zhou, Di wu, Gezheng Xu, Christian Gagné, Eric Eaton

Unlike existing measures which are used as tools to bound the difference of expected risks between tasks (e. g., $\mathcal{H}$-divergence or discrepancy distance), we theoretically show that the performance gap can be viewed as a data- and algorithm-dependent regularizer, which controls the model complexity and leads to finer guarantees.

Representation Learning Transfer Learning