Search Results for author: Yi Zhou

Found 272 papers, 80 papers with code

Data Augmentation for Low-resource Word Segmentation and POS Tagging of Ancient Chinese Texts

no code implementations LT4HALA (LREC) 2022 Yutong Shen, Jiahuan Li, ShuJian Huang, Yi Zhou, Xiaopeng Xie, Qinxin Zhao

Although SikuRoberta significantly boosts performance on WSG and POS tasks on ancient Chinese texts, the lack of labeled data still limits the performance of the model.

Data Augmentation Language Modeling +4

On the Transferability of Adversarial Attacks against Neural Text Classifier

no code implementations EMNLP 2021 Liping Yuan, Xiaoqing Zheng, Yi Zhou, Cho-Jui Hsieh, Kai-Wei Chang

Based on these studies, we propose a genetic algorithm to find an ensemble of models that can be used to induce adversarial examples to fool almost all existing models.

text-classification Text Classification

HUMOTO: A 4D Dataset of Mocap Human Object Interactions

no code implementations14 Apr 2025 Jiaxin Lu, Chun-Hao Paul Huang, Uttaran Bhattacharya, QiXing Huang, Yi Zhou

We present Human Motions with Objects (HUMOTO), a high-fidelity dataset of human-object interactions for motion generation, computer vision, and robotics applications.

Human-Object Interaction Detection Motion Generation +1

Shape My Moves: Text-Driven Shape-Aware Synthesis of Human Motions

no code implementations4 Apr 2025 Ting-Hsuan Liao, Yi Zhou, Yu Shen, Chun-Hao Paul Huang, Saayan Mitra, Jia-Bin Huang, Uttaran Bhattacharya

Additionally, we harness the capabilities of a pretrained language model to predict both continuous shape parameters and motion tokens, facilitating the synthesis of text-aligned motions and decoding them into shape-aware motions.

Language Modeling Language Modelling +3

StrokeFusion: Vector Sketch Generation via Joint Stroke-UDF Encoding and Latent Sequence Diffusion

no code implementations31 Mar 2025 Jin Zhou, Yi Zhou, Pengfei Xu, Hui Huang

It contains a dual-modal sketch feature learning network that maps strokes into a high-quality latent space.

Nested Stochastic Gradient Descent for (Generalized) Sinkhorn Distance-Regularized Distributionally Robust Optimization

no code implementations29 Mar 2025 Yufeng Yang, Yi Zhou, Zhaosong Lu

For this class of regularized DRO problems, we derive a novel dual formulation taking the form of nested stochastic programming, where the dual variable depends on the data sample.

RLDBF: Enhancing LLMs Via Reinforcement Learning With DataBase FeedBack

no code implementations28 Mar 2025 Weichen Dai, Zijie Dai, Zhijie Huang, Yixuan Pan, Xinhe Li, Xi Li, Yi Zhou, Ji Qi, Wu Jiang

While current large language models (LLMs) demonstrate remarkable linguistic capabilities through training on massive unstructured text corpora, they remain inadequate in leveraging structured scientific data (e. g., chemical molecular properties in databases) that encapsulate centuries of accumulated scientific expertise.

reinforcement-learning Reinforcement Learning

Video Motion Graphs

no code implementations26 Mar 2025 Haiyang Liu, Zhan Xu, Fa-Ting Hong, Hsin-Ping Huang, Yi Zhou, Yang Zhou

HMInterp i) employs a dual-branch interpolation approach, combining a Motion Diffusion Model for human skeleton motion interpolation with a diffusion-based video frame interpolation model for final frame generation.

Motion Interpolation Video Frame Interpolation +1

Dual Audio-Centric Modality Coupling for Talking Head Generation

no code implementations26 Mar 2025 Ao Fu, Ziqi Ni, Yi Zhou

The generation of audio-driven talking head videos is a key challenge in computer vision and graphics, with applications in virtual avatars and digital media.

NeRF Talking Head Generation +1

Multiple-Particle Autofocusing Algorithm Using Axial Resolution and Morphological Analyses Based on Digital Holography

no code implementations23 Mar 2025 Wei-Na Li, Yi Zhou, Jiatai Chen, Hongjie Ou, XiangSheng Xie

Based on the mean intensity and equivalent diameter of each candidate focused particle, all focused particles are eventually secured.

Position

Universal Incremental Learning: Mitigating Confusion from Inter- and Intra-task Distribution Randomness

1 code implementation10 Mar 2025 Sheng Luo, Yi Zhou, Tao Zhou

In this work, we investigate $\textbf{Universal Incremental Learning (UIL)}$, where a model neither knows which new classes or domains will increase along sequential tasks, nor the scale of the increments within each task.

Incremental Learning

FREAK: Frequency-modulated High-fidelity and Real-time Audio-driven Talking Portrait Synthesis

no code implementations6 Mar 2025 Ziqi Ni, Ao Fu, Yi Zhou

To address this, we propose a FREquency-modulated, high-fidelity, and real-time Audio-driven talKing portrait synthesis framework, named FREAK, which models talking portraits from the frequency domain perspective, enhancing the fidelity and naturalness of the synthesized portraits.

Audio-Visual Synchronization

Evaluating the Effect of Retrieval Augmentation on Social Biases

no code implementations24 Feb 2025 Tianhui Zhang, Yi Zhou, Danushka Bollegala

Retrieval Augmented Generation (RAG) has gained popularity as a method for conveniently incorporating novel facts that were not seen during the pre-training stage in Large Language Model (LLM)-based Natural Language Generation (NLG) systems.

Question Answering RAG +2

MedMimic: Physician-Inspired Multimodal Fusion for Early Diagnosis of Fever of Unknown Origin

no code implementations7 Feb 2025 Minrui Chen, Yi Zhou, Huidong Jiang, Yuhan Zhu, Guanjie Zou, Minqi Chen, Rong Tian, Hiroto Saigo

By combining the strengths of pretrained large models and deep learning, MedMimic offers a promising solution for disease classification.

Classification Diagnostic

A Post-Processing-Based Fair Federated Learning Framework

no code implementations25 Jan 2025 Yi Zhou, Naman Goel

In the first stage, a global model is trained without fairness constraints using a standard federated learning algorithm (e. g. FedAvg).

Fairness Federated Learning

On Learning Representations for Tabular Data Distillation

no code implementations23 Jan 2025 Inwon Kang, Parikshit Ram, Yi Zhou, Horst Samulowitz, Oshani Seneviratne

Dataset distillation generates a small set of information-rich instances from a large dataset, resulting in reduced storage requirements, privacy or copyright risks, and computational costs for downstream modeling, though much of the research has focused on the image data modality.

Dataset Distillation Representation Learning

Computational Protein Science in the Era of Large Language Models (LLMs)

no code implementations17 Jan 2025 Wenqi Fan, Yi Zhou, Shijie Wang, Yuyao Yan, Hui Liu, Qian Zhao, Le Song, Qing Li

As a result, researchers have actively introduced LLM techniques in computational protein science, developing protein Language Models (pLMs) that skillfully grasp the foundational knowledge of proteins and can be effectively generalized to solve a diversity of sequence-structure-function reasoning problems.

Drug Discovery Protein Design +2

Make Domain Shift a Catastrophic Forgetting Alleviator in Class-Incremental Learning

no code implementations31 Dec 2024 Wei Chen, Yi Zhou

This paper discovers a counter-intuitive observation: by incorporating domain shift into CIL tasks, the forgetting rate is significantly reduced.

class-incremental learning Class Incremental Learning +2

FaceLift: Single Image to 3D Head with View Generation and GS-LRM

no code implementations23 Dec 2024 Weijie Lyu, Yi Zhou, Ming-Hsuan Yang, Zhixin Shu

Our pipeline begins by employing a multi-view latent diffusion model that generates consistent side and back views of the head from a single facial input.

Image Reconstruction Image to 3D +1

DMesh++: An Efficient Differentiable Mesh for Complex Shapes

no code implementations21 Dec 2024 Sanghyun Son, Matheus Gadelha, Yang Zhou, Matthew Fisher, Zexiang Xu, Yi-Ling Qiao, Ming C. Lin, Yi Zhou

Recent probabilistic methods for 3D triangular meshes capture diverse shapes by differentiable mesh connectivity, but face high computational costs with increased shape details.

Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentation

1 code implementation18 Dec 2024 Kaiwen Huang, Tao Zhou, Huazhu Fu, Yizhe Zhang, Yi Zhou, Chen Gong, Dong Liang

In this paper, we propose a learnable prompting SAM-induced Knowledge distillation framework (KnowSAM) for semi-supervised medical image segmentation.

Image Segmentation Knowledge Distillation +3

EvTTC: An Event Camera Dataset for Time-to-Collision Estimation

no code implementations6 Dec 2024 Kaizhen Sun, Jinghang Li, Kuan Dai, Bangyan Liao, Wei Xiong, Yi Zhou

To explore the potential of event cameras in the above-mentioned challenging cases, we propose EvTTC, which is, to the best of our knowledge, the first multi-sensor dataset focusing on TTC tasks under high-relative-speed scenarios.

Data Augmentation

ProteinWeaver: A Divide-and-Assembly Approach for Protein Backbone Design

no code implementations8 Nov 2024 Yiming Ma, Fei Ye, Yi Zhou, Zaixiang Zheng, Dongyu Xue, Quanquan Gu

Comprehensive experiments demonstrate that ProteinWeaver: (1) generates high-quality, novel protein backbones through versatile domain assembly; (2) outperforms RFdiffusion, the current state-of-the-art in backbone design, by 13\% and 39\% for long-chain proteins; (3) shows the potential for cooperative function design through illustrative case studies.

Protein Design

Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey

no code implementations5 Nov 2024 Ao Fu, Yi Zhou, Tao Zhou, Yi Yang, Bojun Gao, Qun Li, Guobin Wu, Ling Shao

World models and video generation are pivotal technologies in the domain of autonomous driving, each playing a critical role in enhancing the robustness and reliability of autonomous systems.

3D Scene Reconstruction Autonomous Driving +1

MAP: Multi-Human-Value Alignment Palette

no code implementations24 Oct 2024 Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar

Ensuring that generative AI systems align with human values is essential but challenging, especially when considering multiple human values and their potential trade-offs.

Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning

1 code implementation20 Oct 2024 Heshan Fernando, Han Shen, Parikshit Ram, Yi Zhou, Horst Samulowitz, Nathalie Baracaldo, Tianyi Chen

Post-training of pre-trained LLMs, which typically consists of the supervised fine-tuning (SFT) stage and the preference learning (RLHF or DPO) stage, is crucial to effective and safe LLM applications.

Adaptive Gradient Normalization and Independent Sampling for (Stochastic) Generalized-Smooth Optimization

no code implementations17 Oct 2024 Yufeng Yang, Erin Tripp, Yifan Sun, Shaofeng Zou, Yi Zhou

Recent studies have shown that many nonconvex machine learning problems satisfy a generalized-smooth condition that extends beyond traditional smooth nonconvex optimization.

ESVO2: Direct Visual-Inertial Odometry with Stereo Event Cameras

1 code implementation12 Oct 2024 Junkai Niu, Sheng Zhong, Xiuyuan Lu, Shaojie Shen, Guillermo Gallego, Yi Zhou

To this end, a compact back-end is proposed for continuously updating the IMU bias and predicting the linear velocity, enabling an accurate motion prediction for camera pose tracking.

motion prediction Pose Tracking +2

CryoFM: A Flow-based Foundation Model for Cryo-EM Densities

no code implementations11 Oct 2024 Yi Zhou, Yilai Li, Jing Yuan, Quanquan Gu

Cryo-electron microscopy (cryo-EM) is a powerful technique in structural biology and drug discovery, enabling the study of biomolecules at high resolution.

Drug Discovery Electron Tomography

Efficient Top-k s-Biplexes Search over Large Bipartite Graphs

no code implementations27 Sep 2024 Zhenxiang Xu, Yiping Liu, Yi Zhou, Yimin Hao, Zhengren Wang

We formulate the problem as the {\em top-$k$ $s$-biplex search (TBS) problem}, which aims to find the top-$k$ maximal $s$-biplexes with the most vertices, where $k$ is an input parameter.

KALE-LM: Unleash The Power Of AI For Science Via Knowledge And Logic Enhanced Large Model

no code implementations27 Sep 2024 Weichen Dai, Yezeng Chen, Zijie Dai, Yubo Liu, Zhijie Huang, Yixuan Pan, Baiyang Song, Chengli Zhong, Xinhe Li, Zeyu Wang, Zhuoying Feng, Yi Zhou

Artificial intelligence is gradually demonstrating its immense potential, and increasing attention is being given to how AI can be harnessed to advance scientific research.

MOSS: Enabling Code-Driven Evolution and Context Management for AI Agents

1 code implementation24 Sep 2024 Ming Zhu, Yi Zhou

MOSS ensures consistency and adaptability by using a mechanism that maintains the Python context across interactions, including isolation of local variables and preservation of runtime integrity.

Code Generation Management

Multi-Modal Diffusion for Hand-Object Grasp Generation

no code implementations6 Sep 2024 Jinkun Cao, Jingyuan Liu, Kris Kitani, Yi Zhou

Compared to previous works of generating hand poses with a given object, we aim to allow the generalization of both hand and object shapes by a single model.

Diversity Grasp Generation +1

COEFF-KANs: A Paradigm to Address the Electrolyte Field with KANs

no code implementations24 Jul 2024 Xinhe Li, Zhuoying Feng, Yezeng Chen, Weichen Dai, Zixu He, Yi Zhou, Shuhong Jiao

Firstly, we adopt the publicly available MoLFormer model to obtain feature vectors for each solvent and salt in the electrolyte.

feature selection

Exploring The Neural Burden In Pruned Models: An Insight Inspired By Neuroscience

no code implementations23 Jul 2024 Zeyu Wang, Weichen Dai, Xiangyu Zhou, Ji Qi, Yi Zhou

Vision Transformer and its variants have been adopted in many visual tasks due to their powerful capabilities, which also bring significant challenges in computation and storage.

A Faster Branching Algorithm for the Maximum $k$-Defective Clique Problem

1 code implementation23 Jul 2024 Chunyu Luo, Yi Zhou, Zhengren Wang, Mingyu Xiao

In the paper, we propose a new branching algorithm that takes advantage of the structural properties of the $k$-defective clique and uses the efficient maximum clique algorithm as a subroutine.

Motion and Structure from Event-based Normal Flow

no code implementations17 Jul 2024 Zhongyang Ren, Bangyan Liao, Delei Kong, Jinghang Li, Peidong Liu, Laurent Kneip, Guillermo Gallego, Yi Zhou

Its success in standard vision is attributed to the maturity of feature extraction, data association and multi-view geometry.

Event-Aided Time-to-Collision Estimation for Autonomous Driving

no code implementations10 Jul 2024 Jinghang Li, Bangyan Liao, Xiuyuan Lu, Peidong Liu, Shaojie Shen, Yi Zhou

Predicting a potential collision with leading vehicles is an essential functionality of any autonomous/assisted driving system.

Autonomous Driving

BeNeRF: Neural Radiance Fields from a Single Blurry Image and Event Stream

1 code implementation2 Jul 2024 Wenpu Li, Pian Wan, Peng Wang, Jinghang Li, Yi Zhou, Peidong Liu

Our method can jointly learn both the implicit neural scene representation and recover the camera motion by minimizing the differences between the synthesized data and the real measurements without pre-computed camera poses from COLMAP.

NeRF

SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cues

1 code implementation27 Jun 2024 Yuxin Xie, Tao Zhou, Yi Zhou, Geng Chen

Weakly-supervised medical image segmentation is a challenging task that aims to reduce the annotation cost while keep the segmentation performance.

Brain Tumor Segmentation Image Segmentation +2

RefXVC: Cross-Lingual Voice Conversion with Enhanced Reference Leveraging

no code implementations24 Jun 2024 Mingyang Zhang, Yi Zhou, Yi Ren, Chen Zhang, Xiang Yin, Haizhou Li

This paper proposes RefXVC, a method for cross-lingual voice conversion (XVC) that leverages reference information to improve conversion performance.

Sentence Voice Conversion

Evaluating Short-Term Temporal Fluctuations of Social Biases in Social Media Data and Masked Language Models

no code implementations19 Jun 2024 Yi Zhou, Danushka Bollegala, Jose Camacho-Collados

Given that MLMs are continuously trained with increasing amounts of additional data collected over time, an important yet unanswered question is how the social biases encoded with MLMs vary over time.

valid

Is Your HD Map Constructor Reliable under Sensor Corruptions?

no code implementations18 Jun 2024 Xiaoshuai Hao, Mengchuan Wei, Yifan Yang, Haimei Zhao, HUI ZHANG, Yi Zhou, Qiang Wang, Weiming Li, Lingdong Kong, Jing Zhang

These insights provide a pathway for developing more reliable HD map construction methods, which are essential for the advancement of autonomous driving technology.

Autonomous Driving Data Augmentation

Multi-Scale Accent Modeling and Disentangling for Multi-Speaker Multi-Accent Text-to-Speech Synthesis

no code implementations16 Jun 2024 Xuehao Zhou, Mingyang Zhang, Yi Zhou, Zhizheng Wu, Haizhou Li

However, accurately and independently modeling both speaker and accent characteristics in text-to-speech (TTS) systems is challenging due to the complex variations of accents and the inherent entanglement between speaker and accent identities.

Disentanglement Speech Synthesis +2

LRM-Zero: Training Large Reconstruction Models with Synthesized Data

1 code implementation13 Jun 2024 Desai Xie, Sai Bi, Zhixin Shu, Kai Zhang, Zexiang Xu, Yi Zhou, Sören Pirk, Arie Kaufman, Xin Sun, Hao Tan

We demonstrate that our LRM-Zero, trained with our fully synthesized Zeroverse, can achieve high visual quality in the reconstruction of real-world objects, competitive with models trained on Objaverse.

3D Reconstruction

Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation

no code implementations3 Jun 2024 Yudan Wang, Yue Wang, Yi Zhou, Shaofeng Zou

Specifically, existing studies show that AC converges to an $\epsilon+\varepsilon_{\text{critic}}$ neighborhood of stationary points with the best known sample complexity of $\mathcal{O}(\epsilon^{-2})$ (up to a log factor), and NAC converges to an $\epsilon+\varepsilon_{\text{critic}}+\sqrt{\varepsilon_{\text{actor}}}$ neighborhood of the global optimum with the best known sample complexity of $\mathcal{O}(\epsilon^{-3})$, where $\varepsilon_{\text{critic}}$ is the approximation error of the critic and $\varepsilon_{\text{actor}}$ is the approximation error induced by the insufficient expressive power of the parameterized policy class.

MM-Retinal: Knowledge-Enhanced Foundational Pretraining with Fundus Image-Text Expertise

1 code implementation20 May 2024 Ruiqi Wu, Chenran Zhang, Jianle Zhang, Yi Zhou, Tao Zhou, Huazhu Fu

Current fundus image analysis models are predominantly built for specific tasks relying on individual datasets.

BugBlitz-AI: An Intelligent QA Assistant

no code implementations17 May 2024 Yi Yao, Jun Wang, Yabai Hu, LiFeng Wang, Yi Zhou, Jack Chen, Xuming Gai, Zhenming Wang, Wenjun Liu

The evolution of software testing from manual to automated methods has significantly influenced quality assurance (QA) practices.

software testing

IMU-Aided Event-based Stereo Visual Odometry

2 code implementations7 May 2024 Junkai Niu, Sheng Zhong, Yi Zhou

In this paper, we improve our previous direct pipeline \textit{Event-based Stereo Visual Odometry} in terms of accuracy and efficiency.

Pose Tracking Visual Odometry

DMesh: A Differentiable Mesh Representation

1 code implementation20 Apr 2024 Sanghyun Son, Matheus Gadelha, Yang Zhou, Zexiang Xu, Ming C. Lin, Yi Zhou

We present a differentiable representation, DMesh, for general 3D triangular meshes.

End-to-End Mesh Optimization of a Hybrid Deep Learning Black-Box PDE Solver

no code implementations17 Apr 2024 Shaocong Ma, James Diffenderfer, Bhavya Kailkhura, Yi Zhou

In this study, we explore the feasibility of end-to-end training of a hybrid model with a black-box PDE solver and a deep learning model for fluid flow prediction.

Deep Learning Graph Neural Network

Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization

no code implementations1 Apr 2024 Qi Zhang, Yi Zhou, Ashley Prater-Bennette, Lixin Shen, Shaofeng Zou

We prove that our algorithm finds an $\epsilon$-stationary point with a computational complexity of $\mathcal O(\epsilon^{-3k_*-5})$, where $k_*$ is the parameter of the Cressie-Read divergence.

Convergence Guarantees for RMSProp and Adam in Generalized-smooth Non-convex Optimization with Affine Noise Variance

no code implementations1 Apr 2024 Qi Zhang, Yi Zhou, Shaofeng Zou

Specifically, to solve the challenges due to dependence among adaptive update, unbounded gradient estimate and Lipschitz constant, we demonstrate that the first-order term in the descent lemma converges and its denominator is upper bounded by a function of gradient norm.

LEMMA

Evaluating Unsupervised Dimensionality Reduction Methods for Pretrained Sentence Embeddings

no code implementations20 Mar 2024 Gaifan Zhang, Yi Zhou, Danushka Bollegala

Sentence embeddings produced by Pretrained Language Models (PLMs) have received wide attention from the NLP community due to their superior performance when representing texts in numerous downstream applications.

Dimensionality Reduction Sentence +1

HIMap: HybrId Representation Learning for End-to-end Vectorized HD Map Construction

no code implementations CVPR 2024 Yi Zhou, HUI ZHANG, Jiaqian Yu, Yifan Yang, Sangil Jung, Seung-In Park, ByungIn Yoo

Concretely, we introduce a hybrid representation called HIQuery to represent all map elements, and propose a point-element interactor to interactively extract and encode the hybrid information of elements, e. g. point position and element shape, into the HIQuery.

Representation Learning

Transfer Learning-Enhanced Instantaneous Multi-Person Indoor Localization by CSI

no code implementations2 Mar 2024 Zhiyuan He, Ke Deng, Jiangchao Gong, Yi Zhou, DeSheng Wang

Passive indoor localization, integral to smart buildings, emergency response, and indoor navigation, has traditionally been limited by a focus on single-target localization and reliance on multi-packet CSI.

Diversity Indoor Localization +1

Brain-Inspired Two-Stage Approach: Enhancing Mathematical Reasoning by Imitating Human Thought Processes

no code implementations23 Feb 2024 Yezeng Chen, Zui Chen, Yi Zhou

Although large language models demonstrate emergent abilities in solving math word problems, there is a challenging task in complex multi-step mathematical reasoning tasks.

Math Mathematical Reasoning

An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning

1 code implementation23 Feb 2024 Zui Chen, Yezeng Chen, Jiaqi Han, Zhijie Huang, Ji Qi, Yi Zhou

Large language models (LLMs) are displaying emergent abilities for math reasoning tasks, and there is a growing attention on enhancing the ability of open-source LLMs through supervised fine-tuning (SFT). In this paper, we aim to explore a general data strategy for supervised data to help optimize and expand math reasoning ability. Firstly, we determine the ability boundary of reasoning paths augmentation by identifying these paths' minimal optimal set. Secondly, we validate that different abilities of the model can be cumulatively enhanced by Mix of Minimal Optimal Sets of corresponding types of data, while our models MMOS achieve SOTA performance on series base models under much lower construction costs. Besides, we point out GSM-HARD is not really hard and today's LLMs no longer lack numerical robustness. Also, we provide an Auto Problem Generator for robustness testing and educational applications. Our code and data are publicly available at https://github. com/cyzhh/MMOS.

Ranked #2 on Math Word Problem Solving on ASDiv-A (using extra training data)

Arithmetic Reasoning Automated Theorem Proving +1

Multimodal-Enhanced Objectness Learner for Corner Case Detection in Autonomous Driving

1 code implementation3 Feb 2024 Lixing Xiao, Ruixiao Shi, Xiaoyang Tang, Yi Zhou

Previous works on object detection have achieved high accuracy in closed-set scenarios, but their performance in open-world scenarios is not satisfactory.

Autonomous Driving Multimodal Deep Learning +1

Enhancing In-context Learning via Linear Probe Calibration

1 code implementation22 Jan 2024 Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen

However, applying ICL in real cases does not scale with the number of samples, and lacks robustness to different prompt templates and demonstration permutations.

In-Context Learning

A Pure Integral-Type PLL with a Damping Branch to Enhance the Stability of Grid-Tied Inverter under Weak Grids

no code implementations4 Jan 2024 Yi Zhou, Zhouchen Deng, Shi Chen, Yiwei Qiu, Tianlei Zang, Buxiang Zhou

In a phase-locked loop (PLL) synchronized inverter, due to the strong nonlinear coupling between the PLL's parame-ters and the operation power angle, the equivalent damping coefficient will quickly deteriorate while the power angle is close to 90{\deg} under an ultra-weak grid, which causes the synchronous instability.

Dual-scale Enhanced and Cross-generative Consistency Learning for Semi-supervised Medical Image Segmentation

1 code implementation26 Dec 2023 Yunqi Gu, Tao Zhou, Yizhe Zhang, Yi Zhou, Kelei He, Chen Gong, Huazhu Fu

To address scale variation, we present a scale-enhanced consistency constraint, which ensures consistency in the segmentation maps generated from the same input image at different scales.

Image Segmentation Segmentation +2

Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning

no code implementations CVPR 2024 Desai Xie, Jiahao Li, Hao Tan, Xin Sun, Zhixin Shu, Yi Zhou, Sai Bi, Sören Pirk, Arie E. Kaufman

To this end, we introduce Carve3D, an improved RLFT algorithm coupled with a novel Multi-view Reconstruction Consistency (MRC) metric, to enhance the consistency of multi-view diffusion models.

Language Modelling Large Language Model +2

Forcing Generative Models to Degenerate Ones: The Power of Data Poisoning Attacks

no code implementations7 Dec 2023 Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Ling Cai, Nathalie Baracaldo

Growing applications of large language models (LLMs) trained by a third party raise serious concerns on the security vulnerability of LLMs. It has been demonstrated that malicious actors can covertly exploit these vulnerabilities in LLMs through poisoning attacks aimed at generating undesirable outputs.

Data Poisoning object-detection +2

Segment Anything Model-guided Collaborative Learning Network for Scribble-supervised Polyp Segmentation

no code implementations1 Dec 2023 Yiming Zhao, Tao Zhou, Yunqi Gu, Yi Zhou, Yizhe Zhang, Ye Wu, Huazhu Fu

Specifically, we first propose a Cross-level Enhancement and Aggregation Network (CEA-Net) for weakly-supervised polyp segmentation.

Segmentation Weakly supervised segmentation

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, 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

Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset

1 code implementation9 Nov 2023 HaoYi Wu, Wenyang Hui, Yezeng Chen, Weiqi Wu, Kewei Tu, Yi Zhou

Since the dataset only involves a narrow range of knowledge, it is easy to separately analyse the knowledge a model possesses and the reasoning ability it has.

Math Natural Language Understanding

A Predictive Factor Analysis of Social Biases and Task-Performance in Pretrained Masked Language Models

no code implementations19 Oct 2023 Yi Zhou, Jose Camacho-Collados, Danushka Bollegala

Various types of social biases have been reported with pretrained Masked Language Models (MLMs) in prior work.

Can Word Sense Distribution Detect Semantic Changes of Words?

1 code implementation16 Oct 2023 Xiaohang Tang, Yi Zhou, Taichi Aida, Procheta Sen, Danushka Bollegala

Given this relationship between WSD and SCD, we explore the possibility of predicting whether a target word has its meaning changed between two corpora collected at different time steps, by comparing the distributions of senses of that word in each corpora.

Change Detection Word Sense Disambiguation

Study on the Time Domain Precision Evolution Mechanism of CNC Machine Tool Feed Systems Based on Acceleration and Deceleration Capability Indicator

no code implementations15 Oct 2023 Xuesong Wang, Yi Zhou, Dongsheng Zhang

This paper innovatively proposes the need to consider the coupling effects among subsystems, directing the optimization design of CNC machine tool feed systems towards time domain dynamic precision.

Philosophy

Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation

no code implementations9 Oct 2023 Yuxiang Lai, Yi Zhou, Xinghong Liu, Tao Zhou

To address these issues, we propose a novel Memory-Assisted Sub-Prototype Mining (MemSPM) method that can learn the differences between samples belonging to the same category and mine sub-classes when there exists significant concept shift between them.

Universal Domain Adaptation

Super Denoise Net: Speech Super Resolution with Noise Cancellation in Low Sampling Rate Noisy Environments

no code implementations9 Oct 2023 Junkang Yang, Hongqing Liu, Lu Gan, Yi Zhou

Speech super-resolution (SSR) aims to predict a high resolution (HR) speech signal from its low resolution (LR) corresponding part.

Denoising Speech Denoising +1

A Tutorial on Uniform B-Spline

no code implementations27 Sep 2023 Yi Zhou

This document facilitates understanding of core concepts about uniform B-spline and its matrix representation.

Edge-aware Feature Aggregation Network for Polyp Segmentation

no code implementations19 Sep 2023 Tao Zhou, Yizhe Zhang, Geng Chen, Yi Zhou, Ye Wu, Deng-Ping Fan

Besides, a Scale-aware Convolution Module (SCM) is proposed to learn scale-aware features by using dilated convolutions with different ratios, in order to effectively deal with scale variation.

Decoder Segmentation

GRIP: Generating Interaction Poses Using Spatial Cues and Latent Consistency

no code implementations22 Aug 2023 Omid Taheri, Yi Zhou, Dimitrios Tzionas, Yang Zhou, Duygu Ceylan, Soren Pirk, Michael J. Black

In contrast, we introduce GRIP, a learning-based method that takes, as input, the 3D motion of the body and the object, and synthesizes realistic motion for both hands before, during, and after object interaction.

Mixed Reality Object

Boosting Multi-modal Model Performance with Adaptive Gradient Modulation

1 code implementation ICCV 2023 Hong Li, Xingyu Li, Pengbo Hu, Yinuo Lei, Chunxiao Li, Yi Zhou

In addition, we find that the jointly trained model typically has a preferred modality on which the competition is weaker than other modalities.

Attribute

Fast Maximum $k$-Plex Algorithms Parameterized by Small Degeneracy Gaps

1 code implementation23 Jun 2023 Zhengren Wang, Yi Zhou, Chunyu Luo, Mingyu Xiao, Jin-Kao Hao

We define a novel parameter of the input instance, $g_k(G)$, the gap between the degeneracy bound and the size of the maximum $k$-plex in the given graph, and present an exact algorithm parameterized by this $g_k(G)$, which has a worst-case running time polynomial in the size of the input graph and exponential in $g_k(G)$.

Community Detection Graph Mining

Multi-Loss Convolutional Network with Time-Frequency Attention for Speech Enhancement

no code implementations15 Jun 2023 Liang Wan, Hongqing Liu, Yi Zhou, Jie Ji

By combining the DPRNN module with Convolution Recurrent Network (CRN), the DPCRN obtained a promising performance in speech separation with a limited model size.

Speech Enhancement Speech Separation

Accented Text-to-Speech Synthesis with Limited Data

no code implementations8 May 2023 Xuehao Zhou, Mingyang Zhang, Yi Zhou, Zhizheng Wu, Haizhou Li

Both objective and subjective evaluation results show that the accented TTS front-end fine-tuned with a small accented phonetic lexicon (5k words) effectively handles the phonetic variation of accents, while the accented TTS acoustic model fine-tuned with a limited amount of accented speech data (approximately 3 minutes) effectively improves the prosodic rendering including pitch and duration.

Speech Synthesis Text to Speech +1

Dual Residual Attention Network for Image Denoising

1 code implementation7 May 2023 Wencong Wu, Shijie Liu, Yi Zhou, Yungang Zhang, Yu Xiang

The proposed DRANet includes two different parallel branches, which can capture complementary features to enhance the learning ability of the model.

 Ranked #1 on Image Denoising on SIDD (Average PSNR metric)

Image Denoising

LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning

no code implementations3 May 2023 Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson

As part of the training, the parties wish to remove unimportant features in the system to improve generalization, efficiency, and explainability.

feature selection Vertical Federated Learning

Can SAM Segment Polyps?

1 code implementation15 Apr 2023 Tao Zhou, Yizhe Zhang, Yi Zhou, Ye Wu, Chen Gong

Recently, Meta AI Research releases a general Segment Anything Model (SAM), which has demonstrated promising performance in several segmentation tasks.

Segmentation

DarkVisionNet: Low-Light Imaging via RGB-NIR Fusion with Deep Inconsistency Prior

1 code implementation13 Mar 2023 Shuangping Jin, Bingbing Yu, Minhao Jing, Yi Zhou, Jiajun Liang, Renhe Ji

To handle this, we propose a new RGB-NIR fusion algorithm called Dark Vision Net (DVN) with two technical novelties: Deep Structure and Deep Inconsistency Prior (DIP).

SSIM

Normal-guided Garment UV Prediction for Human Re-texturing

no code implementations CVPR 2023 Yasamin Jafarian, Tuanfeng Y. Wang, Duygu Ceylan, Jimei Yang, Nathan Carr, Yi Zhou, Hyun Soo Park

To edit human videos in a physically plausible way, a texture map must take into account not only the garment transformation induced by the body movements and clothes fitting, but also its 3D fine-grained surface geometry.

3D Reconstruction Prediction

Self-Paced Learning for Open-Set Domain Adaptation

no code implementations10 Mar 2023 Xinghong Liu, Yi Zhou, Tao Zhou, Jie Qin, Shengcai Liao

Open-set domain adaptation aims to not only recognize target samples belonging to common classes shared by source and target domains but also perceive unknown class samples.

Domain Adaptation

Structure-informed Language Models Are Protein Designers

1 code implementation3 Feb 2023 Zaixiang Zheng, Yifan Deng, Dongyu Xue, Yi Zhou, Fei Ye, Quanquan Gu

This paper demonstrates that language models are strong structure-based protein designers.

TTS-Guided Training for Accent Conversion Without Parallel Data

no code implementations20 Dec 2022 Yi Zhou, Zhizheng Wu, Mingyang Zhang, Xiaohai Tian, Haizhou Li

Specifically, a text-to-speech (TTS) system is first pretrained with target-accented speech data.

Decoder Text to Speech

Cross-view Geo-localization via Learning Disentangled Geometric Layout Correspondence

1 code implementation8 Dec 2022 Xiaohan Zhang, Xingyu Li, Waqas Sultani, Yi Zhou, Safwan Wshah

We attribute this deficiency to the lack of ability to extract the spatial configuration of visual feature layouts and models' overfitting on low-level details from the training set.

Attribute counterfactual +1

Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis

2 code implementations2 Dec 2022 Yonghao Li, Tao Zhou, Kelei He, Yi Zhou, Dinggang Shen

To take advantage of both paired and unpaired data, in this paper, we propose a Multi-scale Transformer Network (MT-Net) with edge-aware pre-training for cross-modality MR image synthesis.

Image Generation Image Imputation +3

Feature Aggregation and Propagation Network for Camouflaged Object Detection

1 code implementation2 Dec 2022 Tao Zhou, Yi Zhou, Chen Gong, Jian Yang, Yu Zhang

In this paper, we propose a novel Feature Aggregation and Propagation Network (FAP-Net) for camouflaged object detection.

Object object-detection +1

On the Curious Case of $\ell_2$ norm of Sense Embeddings

no code implementations26 Oct 2022 Yi Zhou, Danushka Bollegala

We show that the $\ell_2$ norm of a static sense embedding encodes information related to the frequency of that sense in the training corpus used to learn the sense embeddings.

Word Embeddings Word Sense Disambiguation

PARAGEN : A Parallel Generation Toolkit

1 code implementation7 Oct 2022 Jiangtao Feng, Yi Zhou, Jun Zhang, Xian Qian, Liwei Wu, Zhexi Zhang, Yanming Liu, Mingxuan Wang, Lei LI, Hao Zhou

PARAGEN is a PyTorch-based NLP toolkit for further development on parallel generation.

Model Selection

Finite-Time Error Bounds for Greedy-GQ

no code implementations6 Sep 2022 Yue Wang, Yi Zhou, Shaofeng Zou

Our finite-time error bounds match with one of the stochastic gradient descent algorithms for general smooth non-convex optimization problems, despite its additonal challenge in the two time-scale updates.

reinforcement-learning Reinforcement Learning +1

Federated XGBoost on Sample-Wise Non-IID Data

no code implementations3 Sep 2022 Katelinh Jones, Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo

Federated Learning (FL) is a paradigm for jointly training machine learning algorithms in a decentralized manner which allows for parties to communicate with an aggregator to create and train a model, without exposing the underlying raw data distribution of the local parties involved in the training process.

Federated Learning

Learning Visibility for Robust Dense Human Body Estimation

1 code implementation23 Aug 2022 Chun-Han Yao, Jimei Yang, Duygu Ceylan, Yi Zhou, Yang Zhou, Ming-Hsuan Yang

An alternative approach is to estimate dense vertices of a predefined template body in the image space.

A Repulsive Force Unit for Garment Collision Handling in Neural Networks

no code implementations28 Jul 2022 Qingyang Tan, Yi Zhou, Tuanfeng Wang, Duygu Ceylan, Xin Sun, Dinesh Manocha

Despite recent success, deep learning-based methods for predicting 3D garment deformation under body motion suffer from interpenetration problems between the garment and the body.

NeMF: Neural Motion Fields for Kinematic Animation

no code implementations4 Jun 2022 Chengan He, Jun Saito, James Zachary, Holly Rushmeier, Yi Zhou

We present an implicit neural representation to learn the spatio-temporal space of kinematic motions.

Miscellaneous Motion Generation +1

3D-VFD: A Victim-free Detector against 3D Adversarial Point Clouds

no code implementations18 May 2022 Jiahao Zhu, Huajun Zhou, Zixuan Chen, Yi Zhou, Xiaohua Xie

3D deep models consuming point clouds have achieved sound application effects in computer vision.

Adversarial Attack Steganalysis

SHAPE: An Unified Approach to Evaluate the Contribution and Cooperation of Individual Modalities

1 code implementation30 Apr 2022 Pengbo Hu, Xingyu Li, Yi Zhou

Our experiments suggest that for some tasks where different modalities are complementary, the multi-modal models still tend to use the dominant modality alone and ignore the cooperation across modalities.

Data Sampling Affects the Complexity of Online SGD over Dependent Data

no code implementations31 Mar 2022 Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang

Moreover, we show that online SGD with mini-batch sampling can further substantially improve the sample complexity over online SGD with periodic data-subsampling over highly dependent data.

Stochastic Optimization

A Fast and Convergent Proximal Algorithm for Regularized Nonconvex and Nonsmooth Bi-level Optimization

no code implementations30 Mar 2022 Ziyi Chen, Bhavya Kailkhura, Yi Zhou

In this work, we study a proximal gradient-type algorithm that adopts the approximate implicit differentiation (AID) scheme for nonconvex bi-level optimization with possibly nonconvex and nonsmooth regularizers.

Delving into the Estimation Shift of Batch Normalization in a Network

1 code implementation CVPR 2022 Lei Huang, Yi Zhou, Tian Wang, Jie Luo, Xianglong Liu

We define the estimation shift magnitude of BN to quantitatively measure the difference between its estimated population statistics and expected ones.

Sense Embeddings are also Biased--Evaluating Social Biases in Static and Contextualised Sense Embeddings

1 code implementation14 Mar 2022 Yi Zhou, Masahiro Kaneko, Danushka Bollegala

Sense embedding learning methods learn different embeddings for the different senses of an ambiguous word.

Word Embeddings

Extended Load Flexibility of Industrial P2H Plants: A Process Constraint-Aware Scheduling Approach

no code implementations6 Mar 2022 Yiwei Qiu, Buxiang Zhou, Tianlei Zang, Yi Zhou, Ruomei Qi, Jin Lin

The operational flexibility of industrial power-to-hydrogen (P2H) plants enables admittance of volatile renewable power and provides auxiliary regulatory services for the power grid.

Scheduling

Listing Maximal k-Plexes in Large Real-World Graphs

1 code implementation17 Feb 2022 Zhengren Wang, Yi Zhou, Mingyu Xiao, Bakhadyr Khoussainov

Our first contribution is algorithm ListPlex that lists all maximal $k$-plexes in $O^*(\gamma^D)$ time for each constant $k$, where $\gamma$ is a value related to $k$ but strictly smaller than 2, and $D$ is the degeneracy of the graph that is far less than the vertex number $n$ in real-word graphs.

All Community Detection

On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error

no code implementations8 Feb 2022 Quang Minh Nguyen, Hoang H. Nguyen, Yi Zhou, Lam M. Nguyen

In this paper, we propose a novel algorithm based on Gradient Extrapolation Method (GEM-UOT) to find an $\varepsilon$-approximate solution to the UOT problem in $O\big( \kappa \log\big(\frac{\tau n}{\varepsilon}\big) \big)$ iterations with $\widetilde{O}(n^2)$ per-iteration cost, where $\kappa$ is the condition number depending on only the two input measures.

Retrieval

Coordinated Frequency Control through Safe Reinforcement Learning

no code implementations30 Jan 2022 Yi Zhou, Liangcai Zhou, Di Shi, Xiaoying Zhao

With widespread deployment of renewables, the electric power grids are experiencing increasing dynamics and uncertainties, with its secure operation being threatened.

AI Agent Decision Making +4

Accelerated Proximal Alternating Gradient-Descent-Ascent for Nonconvex Minimax Machine Learning

no code implementations22 Dec 2021 Ziyi Chen, Shaocong Ma, Yi Zhou

Alternating gradient-descent-ascent (AltGDA) is an optimization algorithm that has been widely used for model training in various machine learning applications, which aims to solve a nonconvex minimax optimization problem.

BIG-bench Machine Learning

Slot-VPS: Object-centric Representation Learning for Video Panoptic Segmentation

no code implementations CVPR 2022 Yi Zhou, HUI ZHANG, Hana Lee, Shuyang Sun, Pingjun Li, Yangguang Zhu, ByungIn Yoo, Xiaojuan Qi, Jae-Joon Han

We encode all panoptic entities in a video, including both foreground instances and background semantics, with a unified representation called panoptic slots.

Object Representation Learning +1

FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning

no code implementations15 Dec 2021 Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

We address the relatively unexplored problem of hyper-parameter optimization (HPO) for federated learning (FL-HPO).

Federated Learning

Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks

no code implementations21 Nov 2021 Kaiyuan Liu, Xingyu Li, Yurui Lai, Ge Zhang, Hang Su, Jiachen Wang, Chunxu Guo, Jisong Guan, Yi Zhou

Despite its great success, deep learning severely suffers from robustness; that is, deep neural networks are very vulnerable to adversarial attacks, even the simplest ones.

Event-based Motion Segmentation by Cascaded Two-Level Multi-Model Fitting

1 code implementation5 Nov 2021 Xiuyuan Lu, Yi Zhou, Shaojie Shen

In this paper, we present a cascaded two-level multi-model fitting method for identifying independently moving objects (i. e., the motion segmentation problem) with a monocular event camera.

Clustering Motion Segmentation +1

A Cubic Regularization Approach for Finding Local Minimax Points in Nonconvex Minimax Optimization

no code implementations14 Oct 2021 Ziyi Chen, Zhengyang Hu, Qunwei Li, Zhe Wang, Yi Zhou

However, GDA has been proved to converge to stationary points for nonconvex minimax optimization, which are suboptimal compared with local minimax points.

Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy

no code implementations PACLIC 2021 Yi Zhou, Danushka Bollegala

Contextualised word embeddings generated from Neural Language Models (NLMs), such as BERT, represent a word with a vector that considers the semantics of the target word as well its context.

Word Embeddings Word Sense Disambiguation

How to Improve Sample Complexity of SGD over Highly Dependent Data?

no code implementations29 Sep 2021 Shaocong Ma, Ziyi Chen, Yi Zhou, Kaiyi Ji, Yingbin Liang

Specifically, with a $\phi$-mixing model that captures both exponential and polynomial decay of the data dependence over time, we show that SGD with periodic data-subsampling achieves an improved sample complexity over the standard SGD in the full spectrum of the $\phi$-mixing data dependence.

Stochastic Optimization

Escaping Saddle Points in Nonconvex Minimax Optimization via Cubic-Regularized Gradient Descent-Ascent

no code implementations29 Sep 2021 Ziyi Chen, Qunwei Li, Yi Zhou

Our result shows that Cubic-GDA achieves an orderwise faster convergence rate than the standard GDA for a wide spectrum of gradient dominant geometry.

Sample Efficient Stochastic Policy Extragradient Algorithm for Zero-Sum Markov Game

no code implementations ICLR 2022 Ziyi Chen, Shaocong Ma, Yi Zhou

Two-player zero-sum Markov game is a fundamental problem in reinforcement learning and game theory.

Assisted Learning for Organizations with Limited Imbalanced Data

no code implementations20 Sep 2021 Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou

In this work, we develop an assisted learning framework for assisting organizations to improve their learning performance.

Decision Making

Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis

no code implementations8 Sep 2021 Ziyi Chen, Yi Zhou, Rongrong Chen, Shaofeng Zou

Actor-critic (AC) algorithms have been widely adopted in decentralized multi-agent systems to learn the optimal joint control policy.

Specificity-preserving RGB-D Saliency Detection

3 code implementations ICCV 2021 Tao Zhou, Deng-Ping Fan, Geng Chen, Yi Zhou, Huazhu Fu

To effectively fuse cross-modal features in the shared learning network, we propose a cross-enhanced integration module (CIM) and then propagate the fused feature to the next layer for integrating cross-level information.

Decoder object-detection +5

Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble

1 code implementation ACL 2021 Yi Zhou, Xiaoqing Zheng, Cho-Jui Hsieh, Kai-Wei Chang, Xuanjing Huang

Although deep neural networks have achieved prominent performance on many NLP tasks, they are vulnerable to adversarial examples.

Sentence

LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning

no code implementations26 Jul 2021 Kamala Varma, Yi Zhou, Nathalie Baracaldo, Ali Anwar

This global model can be corrupted when Byzantine workers send malicious gradients, which necessitates robust methods for aggregating gradients that mitigate the adverse effects of Byzantine inputs.

Federated Learning

Exploiting Semantic Embedding and Visual Feature for Facial Action Unit Detection

no code implementations CVPR 2021 Huiyuan Yang, Lijun Yin, Yi Zhou, Jiuxiang Gu

The learned AU semantic embeddings are then used as guidance for the generation of attention maps through a cross-modality attention network.

Action Unit Detection Facial Action Unit Detection +1

Improving Entity Linking through Semantic Reinforced Entity Embeddings

1 code implementation ACL 2020 Feng Hou, Ruili Wang, Jun He, Yi Zhou

We propose a simple yet effective method, FGS2EE, to inject fine-grained semantic information into entity embeddings to reduce the distinctiveness and facilitate the learning of contextual commonality.

Entity Embeddings Entity Linking +1

Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation

no code implementations NeurIPS 2021 Yue Wang, Shaofeng Zou, Yi Zhou

Temporal-difference learning with gradient correction (TDC) is a two time-scale algorithm for policy evaluation in reinforcement learning.

reinforcement-learning Reinforcement Learning +1

Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing

no code implementations30 Mar 2021 Cheng Chen, Bhavya Kailkhura, Ryan Goldhahn, Yi Zhou

Federated learning is an emerging data-private distributed learning framework, which, however, is vulnerable to adversarial attacks.

Federated Learning

Multi-Agent Off-Policy TD Learning: Finite-Time Analysis with Near-Optimal Sample Complexity and Communication Complexity

no code implementations24 Mar 2021 Ziyi Chen, Yi Zhou, Rongrong Chen

Under Markovian sampling and linear function approximation, we proved that the finite-time sample complexity of both algorithms for achieving an $\epsilon$-accurate solution is in the order of $\mathcal{O}(\epsilon^{-1}\ln \epsilon^{-1})$, matching the near-optimal sample complexity of centralized TD(0) and TDC.

FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data

no code implementations5 Mar 2021 Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig

We empirically demonstrate the applicability for multiple types of ML models and show a reduction of 10%-70% of training time and 80% to 90% in data transfer with respect to the state-of-the-art approaches.

Federated Learning Privacy Preserving

A Deep Emulator for Secondary Motion of 3D Characters

no code implementations CVPR 2021 Mianlun Zheng, Yi Zhou, Duygu Ceylan, Jernej Barbič

Being a local method, our network is independent of the mesh topology and generalizes to arbitrarily shaped 3D character meshes at test time.

Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification

no code implementations26 Feb 2021 Yi Zhou, Lei Huang, Tianfei Zhou, Ling Shao

For chest X-ray imaging, annotating large-scale data requires professional domain knowledge and is time-consuming.

Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry

no code implementations ICLR 2021 Ziyi Chen, Yi Zhou, Tengyu Xu, Yingbin Liang

By leveraging this Lyapunov function and the K{\L} geometry that parameterizes the local geometries of general nonconvex functions, we formally establish the variable convergence of proximal-GDA to a critical point $x^*$, i. e., $x_t\to x^*, y_t\to y^*(x^*)$.

Global existence for semilinear wave equations with scaling invariant damping in 3-D

no code implementations1 Feb 2021 Ning-An Lai, Yi Zhou

Global existence for small data Cauchy problem of semilinear wave equations with scaling invariant damping in 3-D is established in this work, assuming that the data are radial and the constant in front of the damping belongs to $[1. 5, 2)$.

Analysis of PDEs

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

no code implementations1 Feb 2021 Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan

Data heterogeneity has been identified as one of the key features in federated learning but often overlooked in the lens of robustness to adversarial attacks.

Federated Learning

Visual-Textual Attentive Semantic Consistency for Medical Report Generation

no code implementations ICCV 2021 Yi Zhou, Lei Huang, Tao Zhou, Huazhu Fu, Ling Shao

Second, the progressive report decoder consists of a sentence decoder and a word decoder, where we propose image-sentence matching and description accuracy losses to constrain the visual-textual semantic consistency.

Decoder Medical Report Generation +2

Enhancing Balanced Graph Edge Partition with Effective Local Search

no code implementations17 Dec 2020 Zhenyu Guo, Mingyu Xiao, Yi Zhou, Dongxiang Zhang, Kian-Lee Tan

The graph edge partition problem, which is to split the edge set into multiple balanced parts to minimize the total number of copied vertices, has been widely studied from the view of optimization and algorithms.

Novel Concepts

Event-based Motion Segmentation with Spatio-Temporal Graph Cuts

1 code implementation16 Dec 2020 Yi Zhou, Guillermo Gallego, Xiuyuan Lu, SiQi Liu, Shaojie Shen

We develop a method to identify independently moving objects acquired with an event-based camera, i. e., to solve the event-based motion segmentation problem.

Motion Segmentation Scene Understanding

Canny-VO: Visual Odometry with RGB-D Cameras based on Geometric 3D-2D Edge Alignment

no code implementations15 Dec 2020 Yi Zhou, Hongdong Li, Laurent Kneip

The present paper reviews the classical problem of free-form curve registration and applies it to an efficient RGBD visual odometry system called Canny-VO, as it efficiently tracks all Canny edge features extracted from the images.

Visual Odometry

Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning

no code implementations11 Dec 2020 Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig

This approach makes the use of gradient boosted trees practical in enterprise federated learning.

Federated Learning

Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation

1 code implementation9 Dec 2020 Xueyi Li, Tianfei Zhou, Jianwu Li, Yi Zhou, Zhaoxiang Zhang

We formulate WSSS as a novel group-wise learning task that explicitly models semantic dependencies in a group of images to estimate more reliable pseudo ground-truths, which can be used for training more accurate segmentation models.

Ranked #38 on Weakly-Supervised Semantic Segmentation on COCO 2014 val (using extra training data)

Graph Neural Network Segmentation +3

Mitigating Bias in Federated Learning

no code implementations4 Dec 2020 Annie Abay, Yi Zhou, Nathalie Baracaldo, Shashank Rajamoni, Ebube Chuba, Heiko Ludwig

As methods to create discrimination-aware models develop, they focus on centralized ML, leaving federated learning (FL) unexplored.

Fairness Federated Learning

A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning

no code implementations NeurIPS 2020 Bhavya Kailkhura, Jayaraman J. Thiagarajan, Qunwei Li, Jize Zhang, Yi Zhou, Timo Bremer

Using this framework, we show that space-filling sample designs, such as blue noise and Poisson disk sampling, which optimize spectral properties, outperform random designs in terms of the generalization gap and characterize this gain in a closed-form.

BIG-bench Machine Learning

Contrastive Weight Regularization for Large Minibatch SGD

no code implementations17 Nov 2020 Qiwei Yuan, Weizhe Hua, Yi Zhou, Cunxi Yu

The minibatch stochastic gradient descent method (SGD) is widely applied in deep learning due to its efficiency and scalability that enable training deep networks with a large volume of data.

On the Transferability of Adversarial Attacksagainst Neural Text Classifier

no code implementations17 Nov 2020 Liping Yuan, Xiaoqing Zheng, Yi Zhou, Cho-Jui Hsieh, Kai-Wei Chang

Based on these studies, we propose a genetic algorithm to find an ensemble of models that can be used to induce adversarial examples to fool almost all existing models.

text-classification Text Classification

Neural Network Training Techniques Regularize Optimization Trajectory: An Empirical Study

no code implementations13 Nov 2020 Cheng Chen, Junjie Yang, Yi Zhou

Specifically, we find that the optimization trajectories of successful DNN trainings consistently obey a certain regularity principle that regularizes the model update direction to be aligned with the trajectory direction.

Cross-Lingual Dependency Parsing by POS-Guided Word Reordering

no code implementations Findings of the Association for Computational Linguistics 2020 Lu Liu, Yi Zhou, Jianhan Xu, Xiaoqing Zheng, Kai-Wei Chang, Xuanjing Huang

The words in each sentence of a source language corpus are rearranged to meet the word order in a target language under the guidance of a part-of-speech based language model (LM).

Dependency Parsing Language Modeling +3

Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis

no code implementations NeurIPS 2020 Shaocong Ma, Yi Zhou, Shaofeng Zou

In the Markovian setting, our algorithm achieves the state-of-the-art sample complexity $O(\epsilon^{-1} \log {\epsilon}^{-1})$ that is near-optimal.

Boosting One-Point Derivative-Free Online Optimization via Residual Feedback

no code implementations14 Oct 2020 Yan Zhang, Yi Zhou, Kaiyi Ji, Michael M. Zavlanos

As a result, our regret bounds are much tighter compared to existing regret bounds for ZO with conventional one-point feedback, which suggests that ZO with residual feedback can better track the optimizer of online optimization problems.

UNISON: Unpaired Cross-lingual Image Captioning

no code implementations3 Oct 2020 Jiahui Gao, Yi Zhou, Philip L. H. Yu, Shafiq Joty, Jiuxiang Gu

In this work, we present a novel unpaired cross-lingual method to generate image captions without relying on any caption corpus in the source or the target language.

Caption Generation Image Captioning +3

Group Whitening: Balancing Learning Efficiency and Representational Capacity

1 code implementation CVPR 2021 Lei Huang, Yi Zhou, Li Liu, Fan Zhu, Ling Shao

Results show that GW consistently improves the performance of different architectures, with absolute gains of $1. 02\%$ $\sim$ $1. 49\%$ in top-1 accuracy on ImageNet and $1. 82\%$ $\sim$ $3. 21\%$ in bounding box AP on COCO.

Normalization Techniques in Training DNNs: Methodology, Analysis and Application

no code implementations27 Sep 2020 Lei Huang, Jie Qin, Yi Zhou, Fan Zhu, Li Liu, Ling Shao

Normalization techniques are essential for accelerating the training and improving the generalization of deep neural networks (DNNs), and have successfully been used in various applications.

FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling

no code implementations22 Sep 2020 Cheng Chen, Ziyi Chen, Yi Zhou, Bhavya Kailkhura

We develop FedCluster--a novel federated learning framework with improved optimization efficiency, and investigate its theoretical convergence properties.

Federated Learning

Exploring the Hierarchy in Relation Labels for Scene Graph Generation

no code implementations12 Sep 2020 Yi Zhou, Shuyang Sun, Chao Zhang, Yikang Li, Wanli Ouyang

By assigning each relationship a single label, current approaches formulate the relationship detection as a classification problem.

Graph Generation Relation +2

A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability

no code implementations22 Aug 2020 Yi Zhou, Boyang Wang, Lei Huang, Shanshan Cui, Ling Shao

This dataset has 1, 842 images with pixel-level DR-related lesion annotations, and 1, 000 images with image-level labels graded by six board-certified ophthalmologists with intra-rater consistency.

Lesion Segmentation Transfer Learning

Learning to Generate Diverse Dance Motions with Transformer

no code implementations18 Aug 2020 Jiaman Li, Yihang Yin, Hang Chu, Yi Zhou, Tingwu Wang, Sanja Fidler, Hao Li

We also introduce new evaluation metrics for the quality of synthesized dance motions, and demonstrate that our system can outperform state-of-the-art methods.

Motion Synthesis

Spatio-temporal Attention Model for Tactile Texture Recognition

no code implementations10 Aug 2020 Guanqun Cao, Yi Zhou, Danushka Bollegala, Shan Luo

Recently, tactile sensing has attracted great interest in robotics, especially for facilitating exploration of unstructured environments and effective manipulation.

model

Event-based Stereo Visual Odometry

4 code implementations30 Jul 2020 Yi Zhou, Guillermo Gallego, Shaojie Shen

We present a solution to the problem of visual odometry from the data acquired by a stereo event-based camera rig.

3D Reconstruction Camera Pose Estimation +2

Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle

no code implementations ICML 2020 Shaocong Ma, Yi Zhou

Specifically, minimizer incoherence measures the discrepancy between the global minimizers of a sample loss and those of the total loss and affects the convergence error of SGD with random reshuffle.

Diversity

Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble

1 code implementation20 Jun 2020 Yi Zhou, Xiaoqing Zheng, Cho-Jui Hsieh, Kai-Wei Chang, Xuanjing Huang

Despite neural networks have achieved prominent performance on many natural language processing (NLP) tasks, they are vulnerable to adversarial examples.

Sentence

A New One-Point Residual-Feedback Oracle For Black-Box Learning and Control

no code implementations18 Jun 2020 Yan Zhang, Yi Zhou, Kaiyi Ji, Michael M. Zavlanos

When optimizing a deterministic Lipschitz function, we show that the query complexity of ZO with the proposed one-point residual feedback matches that of ZO with the existing two-point schemes.

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