Search Results for author: Xiao Li

Found 137 papers, 38 papers with code

Capturing Conversational Interaction for Question Answering via Global History Reasoning

1 code implementation Findings (NAACL) 2022 Jin Qian, Bowei Zou, Mengxing Dong, Xiao Li, AiTi Aw, Yu Hong

Conversational Question Answering (ConvQA) is required to answer the current question, conditioned on the observable paragraph-level context and conversation history.

Conversational Question Answering

PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition

1 code implementation15 Jul 2024 Xiao Li, Yining Liu, Na Dong, Sitian Qin, Xiaolin Hu

With these annotations, we build part-based methods directly on the standard IN-1K dataset for robust recognition.

Adversarial Robustness Inductive Bias +1

A Generalized Version of Chung's Lemma and its Applications

no code implementations9 Jun 2024 Li Jiang, Xiao Li, Andre Milzarek, Junwen Qiu

Chung's lemma is a classical tool for establishing asymptotic convergence rates of (stochastic) optimization methods under strong convexity-type assumptions and appropriate polynomial diminishing step sizes.

LEMMA Stochastic Optimization

A KL-based Analysis Framework with Applications to Non-Descent Optimization Methods

no code implementations4 Jun 2024 Junwen Qiu, Bohao Ma, Xiao Li, Andre Milzarek

We propose a novel analysis framework for non-descent-type optimization methodologies in nonconvex scenarios based on the Kurdyka-Lojasiewicz property.

Distributed Optimization

Robust Knowledge Distillation Based on Feature Variance Against Backdoored Teacher Model

1 code implementation1 Jun 2024 Jinyin Chen, Xiaoming Zhao, Haibin Zheng, Xiao Li, Sheng Xiang, Haifeng Guo

Knowledge distillation (KD) is one of the widely used compression techniques for edge deployment, by obtaining a lightweight student model from a well-trained teacher model released on public platforms.

Knowledge Distillation Model Compression

Leveraging Generative AI for Smart City Digital Twins: A Survey on the Autonomous Generation of Data, Scenarios, 3D City Models, and Urban Designs

no code implementations29 May 2024 Haowen Xu, Femi Omitaomu, Soheil Sabri, Xiao Li, Yongze Song

The digital transformation of modern cities by integrating advanced information, communication, and computing technologies has marked the epoch of data-driven smart city applications for efficient and sustainable urban management.

Code Generation Data Augmentation +1

RaFe: Ranking Feedback Improves Query Rewriting for RAG

no code implementations23 May 2024 Shengyu Mao, Yong Jiang, Boli Chen, Xiao Li, Peng Wang, Xinyu Wang, Pengjun Xie, Fei Huang, Huajun Chen, Ningyu Zhang

As Large Language Models (LLMs) and Retrieval Augmentation Generation (RAG) techniques have evolved, query rewriting has been widely incorporated into the RAG system for downstream tasks like open-domain QA.

RAG Retrieval

Machine Learning Techniques for Data Reduction of Climate Applications

no code implementations1 May 2024 Xiao Li, Qian Gong, Jaemoon Lee, Scott Klasky, Anand Rangarajan, Sanjay Ranka

Scientists conduct large-scale simulations to compute derived quantities-of-interest (QoI) from primary data.

A Minimal Set of Parameters Based Depth-Dependent Distortion Model and Its Calibration Method for Stereo Vision Systems

no code implementations30 Apr 2024 Xin Ma, Puchen Zhu, Xiao Li, Xiaoyin Zheng, Jianshu Zhou, Xuchen Wang, Kwok Wai Samuel Au

In this work, we propose a minimal set of parameters based depth-dependent distortion model (MDM), which considers the radial and decentering distortions of the lens to improve the accuracy of stereo vision systems and simplify their calibration process.

Machine Learning Techniques for Data Reduction of CFD Applications

no code implementations28 Apr 2024 Jaemoon Lee, Ki Sung Jung, Qian Gong, Xiao Li, Scott Klasky, Jacqueline Chen, Anand Rangarajan, Sanjay Ranka

We present an approach called guaranteed block autoencoder that leverages Tensor Correlations (GBATC) for reducing the spatiotemporal data generated by computational fluid dynamics (CFD) and other scientific applications.

Semantic Satellite Communications Based on Generative Foundation Model

no code implementations18 Apr 2024 Peiwen Jiang, Chao-Kai Wen, Xiao Li, Shi Jin, Geoffrey Ye Li

Considering the high speed of satellites, an adaptive encoder-decoder is proposed to protect important features and avoid frequent retransmissions.

Decoder Semantic Communication

Exploring Key Point Analysis with Pairwise Generation and Graph Partitioning

1 code implementation17 Apr 2024 Xiao Li, Yong Jiang, Shen Huang, Pengjun Xie, Gong Cheng, Fei Huang

Our objective is to train a generative model that can simultaneously provide a score indicating the presence of shared key point between a pair of arguments and generate the shared key point.

Argument Mining graph partitioning +2

BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models

1 code implementation3 Apr 2024 Qijun Luo, Hengxu Yu, Xiao Li

The results demonstrate that BAdam is capable of narrowing the performance gap with Adam more effectively than LoRA.

Autonomous Driving With Perception Uncertainties: Deep-Ensemble Based Adaptive Cruise Control

no code implementations22 Mar 2024 Xiao Li, H. Eric Tseng, Anouck Girard, Ilya Kolmanovsky

In the scenario of Adaptive Cruise Control (ACC), we employ the Deep Ensemble to estimate distance headway to the lead vehicle from RGB images and enable the downstream controller to account for the estimation uncertainty.

Autonomous Driving Decision Making +1

RCoCo: Contrastive Collective Link Prediction across Multiplex Network in Riemannian Space

no code implementations4 Mar 2024 Li Sun, Mengjie Li, Yong Yang, Xiao Li, Lin Liu, Pengfei Zhang, Haohua Du

Annotating anchor users is laborious and expensive, and thus it is impractical to work with quantities of anchor users.

Graph Attention Link Prediction

FormulaReasoning: A Dataset for Formula-Based Numerical Reasoning

2 code implementations20 Feb 2024 Xiao Li, Bolin Zhu, Sichen Liu, Yin Zhu, Yiwei Liu, Gong Cheng

The application of formulas is a fundamental ability of humans when addressing numerical reasoning problems.

Data Augmentation High School Physics +2

System-level Safety Guard: Safe Tracking Control through Uncertain Neural Network Dynamics Models

1 code implementation11 Dec 2023 Xiao Li, Yutong Li, Anouck Girard, Ilya Kolmanovsky

The Neural Network (NN), as a black-box function approximator, has been considered in many control and robotics applications.

Robot Navigation

A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization

no code implementations2 Dec 2023 Junwen Qiu, Xiao Li, Andre Milzarek

In this work, we design a new normal map-based proximal random reshuffling (norm-PRR) method for nonsmooth nonconvex finite-sum problems.

Stochastic Optimization

Low-Complexity Joint Beamforming for RIS-Assisted MU-MISO Systems Based on Model-Driven Deep Learning

no code implementations26 Nov 2023 Weijie Jin, Jing Zhang, Chao-Kai Wen, Shi Jin, Xiao Li, Shuangfeng Han

Reconfigurable intelligent surfaces (RIS) can improve signal propagation environments by adjusting the phase of the incident signal.

Stochastic Optimization

High Probability Guarantees for Random Reshuffling

no code implementations20 Nov 2023 Hengxu Yu, Xiao Li

This criterion is guaranteed to be triggered after a finite number of iterations, and then $\mathsf{RR}$-$\mathsf{sc}$ returns an iterate with its gradient below $\varepsilon$ with high probability.

Missing Value Imputation for Multi-attribute Sensor Data Streams via Message Propagation (Extended Version)

1 code implementation13 Nov 2023 Xiao Li, Huan Li, Hua Lu, Christian S. Jensen, Varun Pandey, Volker Markl

First, we propose a message propagation imputation network (MPIN) that is able to recover the missing values of data instances in a time window.

Attribute Imputation

Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination

1 code implementation6 Nov 2023 Peng Wang, Xiao Li, Can Yaras, Zhihui Zhu, Laura Balzano, Wei Hu, Qing Qu

To the best of our knowledge, this is the first quantitative characterization of feature evolution in hierarchical representations of deep linear networks.

Feature Compression Multi-class Classification +2

Modeling and Control of Diesel Engine Emissions using Multi-layer Neural Networks and Economic Model Predictive Control

no code implementations6 Nov 2023 Jiadi Zhang, Xiao Li, Mohammad Reza Amini, Ilya Kolmanovsky, Munechika Tsutsumi, Hayato Nakada

This paper presents the results of developing a multi-layer Neural Network (NN) to represent diesel engine emissions and integrating this NN into control design.

Model Predictive Control

Model Predictive Control of Diesel Engine Emissions Based on Neural Network Modeling

no code implementations6 Nov 2023 Jiadi Zhang, Xiao Li, Ilya Kolmanovsky, Munechika Tsutsumi, Hayato Nakada

The developments described in the paper are based on a high-fidelity model of the engine airpath and torque response in GT-Power, which is extended with a feedforward neural network (FNN)-based model of engine out (feedgas) emissions identified from experimental engine data to enable the controller co-simulation and performance verification.

Model Predictive Control

Neural Collapse in Multi-label Learning with Pick-all-label Loss

1 code implementation24 Oct 2023 Pengyu Li, Xiao Li, Yutong Wang, Qing Qu

We study deep neural networks for the multi-label classification (MLab) task through the lens of neural collapse (NC).

Multi-class Classification Multi-Label Classification +2

A Deep Instance Generative Framework for MILP Solvers Under Limited Data Availability

1 code implementation NeurIPS 2023 Zijie Geng, Xijun Li, Jie Wang, Xiao Li, Yongdong Zhang, Feng Wu

In the past few years, there has been an explosive surge in the use of machine learning (ML) techniques to address combinatorial optimization (CO) problems, especially mixed-integer linear programs (MILPs).

Combinatorial Optimization

Interaction-Aware Decision-Making for Autonomous Vehicles in Forced Merging Scenario Leveraging Social Psychology Factors

no code implementations25 Sep 2023 Xiao Li, Kaiwen Liu, H. Eric Tseng, Anouck Girard, Ilya Kolmanovsky

Understanding the intention of vehicles in the surrounding traffic is crucial for an autonomous vehicle to successfully accomplish its driving tasks in complex traffic scenarios such as highway forced merging.

Autonomous Vehicles Decision Making

Semantic Communications using Foundation Models: Design Approaches and Open Issues

no code implementations23 Sep 2023 Peiwen Jiang, Chao-Kai Wen, Xinping Yi, Xiao Li, Shi Jin, Jun Zhang

Foundation models (FMs), including large language models, have become increasingly popular due to their wide-ranging applicability and ability to understand human-like semantics.

Investigating the Catastrophic Forgetting in Multimodal Large Language Models

no code implementations19 Sep 2023 Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, Yi Ma

However, catastrophic forgetting, a notorious phenomenon where the fine-tuned model fails to retain similar performance compared to the pre-trained model, still remains an inherent problem in multimodal LLMs (MLLM).

Image Classification Language Modelling +2

Multi-step prediction of chlorophyll concentration based on Adaptive Graph-Temporal Convolutional Network with Series Decomposition

no code implementations13 Sep 2023 Ying Chen, Xiao Li, Hongbo Zhang, Wenyang Song, Chongxuan Xv

The adaptive graph convolution learns the relationship between different water quality parameters, updates the state information of each parameter, and improves the learning ability of the update relationship between nodes.

Decision Making

Chat2Brain: A Method for Mapping Open-Ended Semantic Queries to Brain Activation Maps

no code implementations10 Sep 2023 Yaonai Wei, Tuo Zhang, Han Zhang, Tianyang Zhong, Lin Zhao, Zhengliang Liu, Chong Ma, Songyao Zhang, Muheng Shang, Lei Du, Xiao Li, Tianming Liu, Junwei Han

In this study, we propose a method called Chat2Brain that combines LLMs to basic text-2-image model, known as Text2Brain, to map open-ended semantic queries to brain activation maps in data-scarce and complex query environments.

A Spatiotemporal Correspondence Approach to Unsupervised LiDAR Segmentation with Traffic Applications

no code implementations23 Aug 2023 Xiao Li, Pan He, Aotian Wu, Sanjay Ranka, Anand Rangarajan

We address the problem of unsupervised semantic segmentation of outdoor LiDAR point clouds in diverse traffic scenarios.

Clustering Pseudo Label +3

Efficient View Synthesis with Neural Radiance Distribution Field

no code implementations ICCV 2023 Yushuang Wu, Xiao Li, Jinglu Wang, Xiaoguang Han, Shuguang Cui, Yan Lu

Specifically, we use a small network similar to NeRF while preserving the rendering speed with a single network forwarding per pixel as in NeLF.

Spatially Varying Nanophotonic Neural Networks

no code implementations7 Aug 2023 Kaixuan Wei, Xiao Li, Johannes Froech, PRANEETH CHAKRAVARTHULA, James Whitehead, Ethan Tseng, Arka Majumdar, Felix Heide

The explosive growth of computation and energy cost of artificial intelligence has spurred strong interests in new computing modalities as potential alternatives to conventional electronic processors.

2k

Thin On-Sensor Nanophotonic Array Cameras

no code implementations5 Aug 2023 PRANEETH CHAKRAVARTHULA, Jipeng Sun, Xiao Li, Chenyang Lei, Gene Chou, Mario Bijelic, Johannes Froesch, Arka Majumdar, Felix Heide

The optical array is embedded on a metasurface that, at 700~nm height, is flat and sits on the sensor cover glass at 2. 5~mm focal distance from the sensor.

The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI

no code implementations1 Jun 2023 Ahmed W. Moawad, Anastasia Janas, Ujjwal Baid, Divya Ramakrishnan, Rachit Saluja, Nader Ashraf, Leon Jekel, Raisa Amiruddin, Maruf Adewole, Jake Albrecht, Udunna Anazodo, Sanjay Aneja, Syed Muhammad Anwar, Timothy Bergquist, Evan Calabrese, Veronica Chiang, Verena Chung, Gian Marco Marco Conte, Farouk Dako, James Eddy, Ivan Ezhov, Ariana Familiar, Keyvan Farahani, Juan Eugenio Iglesias, Zhifan Jiang, Elaine Johanson, Anahita Fathi Kazerooni, Florian Kofler, Kiril Krantchev, Dominic LaBella, Koen van Leemput, Hongwei Bran Li, Marius George Linguraru, Katherine E. Link, Xinyang Liu, Nazanin Maleki, Zeke Meier, Bjoern H Menze, Harrison Moy, Klara Osenberg, Marie Piraud, Zachary Reitman, Russel Takeshi Shinohara, Nourel Hoda Tahon, Ayman Nada, Yuri S. Velichko, Chunhao Wang, Benedikt Wiestler, Walter Wiggins, Umber Shafique, Arman Avesta, Khaled Bousabarah, Satrajit Chakrabarty, Nicolo Gennaro, Wolfgang Holler, Manpreet Kaur, Pamela Lamontagne, MingDe Lin, Jan Lost, Daniel S. Marcus, Ryan Maresca, Sarah Merkaj, Ayaman Nada, Gabriel Cassinelli Pedersen, Marc von Reppert, Aristeidis Sotiras, Oleg Teytelboym, Niklas Tillmans, Malte Westerhoff, Ayda Youssef, Devon Godfrey, Scott Floyd, Andreas Rauschecker, Javier Villanueva-Meyer, Irada Pflüger, Jaeyoung Cho, Martin Bendszus, Gianluca Brugnara, Justin Cramer, Gloria J. Guzman Perez-Carillo, Derek R. Johnson, Anthony Kam, Benjamin Yin Ming Kwan, Lillian Lai, Neil U. Lall, Fatima Memon, Satya Narayana Patro, Bojan Petrovic, Tiffany Y. So, Gerard Thompson, Lei Wu, E. Brooke Schrickel, Anu Bansal, Frederik Barkhof, Cristina Besada, Sammy Chu, Jason Druzgal, Alexandru Dusoi, Luciano Farage, Fabricio Feltrin, Amy Fong, Steve H. Fung, R. Ian Gray, Ichiro Ikuta, Michael Iv, Alida A. Postma, Amit Mahajan, David Joyner, Chase Krumpelman, Laurent Letourneau-Guillon, Christie M. Lincoln, Mate E. Maros, Elka Miller, Fanny Morón, Esther A. Nimchinsky, Ozkan Ozsarlak, Uresh Patel, Saurabh Rohatgi, Atin Saha, Anousheh Sayah, Eric D. Schwartz, Robert Shih, Mark S. Shiroishi, Juan E. Small, Manoj Tanwar, Jewels Valerie, Brent D. Weinberg, Matthew L. White, Robert Young, Vahe M. Zohrabian, Aynur Azizova, Melanie Maria Theresa Brüßeler, Pascal Fehringer, Mohanad Ghonim, Mohamed Ghonim, Athanasios Gkampenis, Abdullah Okar, Luca Pasquini, Yasaman Sharifi, Gagandeep Singh, Nico Sollmann, Theodora Soumala, Mahsa Taherzadeh, Nikolay Yordanov, Philipp Vollmuth, Martha Foltyn-Dumitru, Ajay Malhotra, Aly H. Abayazeed, Francesco Dellepiane, Philipp Lohmann, Víctor M. Pérez-García, Hesham Elhalawani, Sanaria Al-Rubaiey, Rui Duarte Armindo, Kholod Ashraf, Moamen M. Asla, Mohamed Badawy, Jeroen Bisschop, Nima Broomand Lomer, Jan Bukatz, Jim Chen, Petra Cimflova, Felix Corr, Alexis Crawley, Lisa Deptula, Tasneem Elakhdar, Islam H. Shawali, Shahriar Faghani, Alexandra Frick, Vaibhav Gulati, Muhammad Ammar Haider, Fátima Hierro, Rasmus Holmboe Dahl, Sarah Maria Jacobs, Kuang-chun Jim Hsieh, Sedat G. Kandemirli, Katharina Kersting, Laura Kida, Sofia Kollia, Ioannis Koukoulithras, Xiao Li, Ahmed Abouelatta, Aya Mansour, Ruxandra-Catrinel Maria-Zamfirescu, Marcela Marsiglia, Yohana Sarahi Mateo-Camacho, Mark McArthur, Olivia McDonnell, Maire McHugh, Mana Moassefi, Samah Mostafa Morsi, Alexander Muntenu, Khanak K. Nandolia, Syed Raza Naqvi, Yalda Nikanpour, Mostafa Alnoury, Abdullah Mohamed Aly Nouh, Francesca Pappafava, Markand D. Patel, Samantha Petrucci, Eric Rawie, Scott Raymond, Borna Roohani, Sadeq Sabouhi, Laura M. Sanchez-Garcia, Zoe Shaked, Pokhraj P. Suthar, Talissa Altes, Edvin Isufi, Yaseen Dhermesh, Jaime Gass, Jonathan Thacker, Abdul Rahman Tarabishy, Benjamin Turner, Sebastiano Vacca, George K. Vilanilam, Daniel Warren, David Weiss, Klara Willms, Fikadu Worede, Sara Yousry, Wondwossen Lerebo, Alejandro Aristizabal, Alexandros Karargyris, Hasan Kassem, Sarthak Pati, Micah Sheller, Spyridon Bakas, Jeffrey D. Rudie, Mariam Aboian

Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing.

Benchmarking Brain Tumor Segmentation +4

On the Importance of Backbone to the Adversarial Robustness of Object Detectors

no code implementations27 May 2023 Xiao Li, Hang Chen, Xiaolin Hu

We argue that using adversarially pre-trained backbone networks is essential for enhancing the adversarial robustness of object detectors.

Adversarial Robustness Autonomous Driving +3

ReSync: Riemannian Subgradient-based Robust Rotation Synchronization

1 code implementation NeurIPS 2023 Huikang Liu, Xiao Li, Anthony Man-Cho So

This work presents ReSync, a Riemannian subgradient-based algorithm for solving the robust rotation synchronization problem, which arises in various engineering applications.

Revisiting Subgradient Method: Complexity and Convergence Beyond Lipschitz Continuity

no code implementations23 May 2023 Xiao Li, Lei Zhao, Daoli Zhu, Anthony Man-Cho So

In particular, when $f$ is convex, we show $\mathcal{O}(\log(k)/\sqrt{k})$ rate of convergence in terms of the suboptimality gap.

Two-shot Video Object Segmentation

1 code implementation CVPR 2023 Kun Yan, Xiao Li, Fangyun Wei, Jinglu Wang, Chenbin Zhang, Ping Wang, Yan Lu

The underlying idea is to generate pseudo labels for unlabeled frames during training and to optimize the model on the combination of labeled and pseudo-labeled data.

Object Pseudo Label +5

Structural Multiplane Image: Bridging Neural View Synthesis and 3D Reconstruction

no code implementations CVPR 2023 Mingfang Zhang, Jinglu Wang, Xiao Li, Yifei HUANG, Yoichi Sato, Yan Lu

The Multiplane Image (MPI), containing a set of fronto-parallel RGBA layers, is an effective and efficient representation for view synthesis from sparse inputs.

3D Reconstruction

A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection in OFDM Systems

1 code implementation7 Mar 2023 Haocheng Ju, Haimiao Zhang, Lin Li, Xiao Li, Bin Dong

Joint channel estimation and signal detection (JCESD) is crucial in orthogonal frequency division multiplexing (OFDM) systems, but traditional algorithms perform poorly in low signal-to-noise ratio (SNR) scenarios.

Rolling Shutter Correction

Distributed Stochastic Optimization under a General Variance Condition

no code implementations30 Jan 2023 Kun Huang, Xiao Li, Shi Pu

Distributed stochastic optimization has drawn great attention recently due to its effectiveness in solving large-scale machine learning problems.

Stochastic Optimization

Language-Driven Anchors for Zero-Shot Adversarial Robustness

1 code implementation CVPR 2024 Xiao Li, Wei zhang, Yining Liu, Zhanhao Hu, Bo Zhang, Xiaolin Hu

Previous researches mainly focus on improving adversarial robustness in the fully supervised setting, leaving the challenging domain of zero-shot adversarial robustness an open question.

Adversarial Defense Adversarial Robustness +3

A Provable Splitting Approach for Symmetric Nonnegative Matrix Factorization

no code implementations25 Jan 2023 Xiao Li, Zhihui Zhu, Qiuwei Li, Kai Liu

The symmetric Nonnegative Matrix Factorization (NMF), a special but important class of the general NMF, has found numerous applications in data analysis such as various clustering tasks.

Clustering Image Clustering +1

An Efficient Semi-Automated Scheme for Infrastructure LiDAR Annotation

no code implementations25 Jan 2023 Aotian Wu, Pan He, Xiao Li, Ke Chen, Sanjay Ranka, Anand Rangarajan

Specifically, we introduce a human-in-the-loop schema in which annotators recursively fix and refine annotations imperfectly predicted by our tool and incrementally add them to the training dataset to obtain better SOT and MOT models.

Autonomous Driving Multi-Object Tracking +4

Principled and Efficient Transfer Learning of Deep Models via Neural Collapse

no code implementations23 Dec 2022 Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu

As model size continues to grow and access to labeled training data remains limited, transfer learning has become a popular approach in many scientific and engineering fields.

Data Augmentation Self-Supervised Learning +1

DyRRen: A Dynamic Retriever-Reranker-Generator Model for Numerical Reasoning over Tabular and Textual Data

1 code implementation23 Nov 2022 Xiao Li, Yin Zhu, Sichen Liu, Jiangzhou Ju, Yuzhong Qu, Gong Cheng

Numerical reasoning over hybrid data containing tables and long texts has recently received research attention from the AI community.

Math Retrieval

Estimating Neural Reflectance Field from Radiance Field using Tree Structures

no code implementations9 Oct 2022 Xiu Li, Xiao Li, Yan Lu

A high-quality NeRF decomposition relies on good geometry information extraction as well as good prior terms to properly resolve ambiguities between different components.

Are All Losses Created Equal: A Neural Collapse Perspective

no code implementations4 Oct 2022 Jinxin Zhou, Chong You, Xiao Li, Kangning Liu, Sheng Liu, Qing Qu, Zhihui Zhu

We extend such results and show through global solution and landscape analyses that a broad family of loss functions including commonly used label smoothing (LS) and focal loss (FL) exhibits Neural Collapse.

Neural Capture of Animatable 3D Human from Monocular Video

no code implementations18 Aug 2022 Gusi Te, Xiu Li, Xiao Li, Jinglu Wang, Wei Hu, Yan Lu

We present a novel paradigm of building an animatable 3D human representation from a monocular video input, such that it can be rendered in any unseen poses and views.

On the Privacy Effect of Data Enhancement via the Lens of Memorization

1 code implementation17 Aug 2022 Xiao Li, Qiongxiu Li, Zhanhao Hu, Xiaolin Hu

We demonstrate that the generalization gap and privacy leakage are less correlated than those of the previous results.

Adversarial Robustness Data Augmentation +1

Randomized Coordinate Subgradient Method for Nonsmooth Composite Optimization

no code implementations30 Jun 2022 Lei Zhao, Ding Chen, Daoli Zhu, Xiao Li

For the case when $f$ is weakly convex and its subdifferential satisfies the global metric subregularity property, we derive the $\mathcal{O}(\varepsilon^{-4})$ iteration complexity in expectation.

LEMMA

AI for CSI Feedback Enhancement in 5G-Advanced

no code implementations30 Jun 2022 Jiajia Guo, Chao-Kai Wen, Shi Jin, Xiao Li

This article provides a guideline for the standardization study of AI-based CSI feedback enhancement.

Finite-Time Analysis of Fully Decentralized Single-Timescale Actor-Critic

no code implementations12 Jun 2022 Qijun Luo, Xiao Li

Most of the existing finite-time convergence results are derived based on either double-loop update or two-timescale step sizes rule, and this is the case even for centralized AC algorithm under a single-agent setting.

Multi-agent Reinforcement Learning Privacy Preserving

A Unified Convergence Theorem for Stochastic Optimization Methods

no code implementations8 Jun 2022 Xiao Li, Andre Milzarek

In this work, we provide a fundamental unified convergence theorem used for deriving expected and almost sure convergence results for a series of stochastic optimization methods.

Stochastic Optimization

On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features

no code implementations2 Mar 2022 Jinxin Zhou, Xiao Li, Tianyu Ding, Chong You, Qing Qu, Zhihui Zhu

When training deep neural networks for classification tasks, an intriguing empirical phenomenon has been widely observed in the last-layer classifiers and features, where (i) the class means and the last-layer classifiers all collapse to the vertices of a Simplex Equiangular Tight Frame (ETF) up to scaling, and (ii) cross-example within-class variability of last-layer activations collapses to zero.

Distributed Random Reshuffling over Networks

no code implementations31 Dec 2021 Kun Huang, Xiao Li, Andre Milzarek, Shi Pu, Junwen Qiu

We show that D-RR inherits favorable characteristics of RR for both smooth strongly convex and smooth nonconvex objective functions.

Distributed Optimization

Reliable Propagation-Correction Modulation for Video Object Segmentation

1 code implementation6 Dec 2021 Xiaohao Xu, Jinglu Wang, Xiao Li, Yan Lu

We introduce two modulators, propagation and correction modulators, to separately perform channel-wise re-calibration on the target frame embeddings according to local temporal correlations and reliable references respectively.

Object Semantic Segmentation +2

Hybrid Instance-aware Temporal Fusion for Online Video Instance Segmentation

no code implementations3 Dec 2021 Xiang Li, Jinglu Wang, Xiao Li, Yan Lu

Based on this representation, we introduce a cropping-free temporal fusion approach to model the temporal consistency between video frames.

Image Segmentation Instance Segmentation +2

BarrierNet: A Safety-Guaranteed Layer for Neural Networks

no code implementations22 Nov 2021 Wei Xiao, Ramin Hasani, Xiao Li, Daniela Rus

This paper introduces differentiable higher-order control barrier functions (CBF) that are end-to-end trainable together with learning systems.

Video Instance Segmentation by Instance Flow Assembly

no code implementations20 Oct 2021 Xiang Li, Jinglu Wang, Xiao Li, Yan Lu

Instance segmentation is a challenging task aiming at classifying and segmenting all object instances of specific classes.

Instance Segmentation Object +3

Convergence of Random Reshuffling Under The Kurdyka-Łojasiewicz Inequality

no code implementations10 Oct 2021 Xiao Li, Andre Milzarek, Junwen Qiu

We conduct a novel convergence analysis for the non-descent RR method with diminishing step sizes based on the KL inequality, which generalizes the standard KL framework.

SeanNet: Semantic Understanding Network for Localization Under Object Dynamics

1 code implementation5 Oct 2021 Xiao Li, Yidong Du, Zhen Zeng, Odest Chadwicke Jenkins

This paper proposes a SEmantic understANding Network (SeanNet) architecture that enables an effective learning process with coupled visual and semantic inputs.

Contrastive Learning Object +1

Randomized Primal-Dual Coordinate Method for Large-scale Linearly Constrained Nonsmooth Nonconvex Optimization

no code implementations29 Sep 2021 Lei Zhao, Daoli Zhu, Xiao Li

The large-scale linearly constrained nonsmooth nonconvex optimization finds wide applications in machine learning, including non-PSD Kernel SVM, linearly constrained Lasso with nonsmooth nonconvex penalty, etc.

End-to-End Video Object Detection with Spatial-Temporal Transformers

1 code implementation23 May 2021 Lu He, Qianyu Zhou, Xiangtai Li, Li Niu, Guangliang Cheng, Xiao Li, Wenxuan Liu, Yunhai Tong, Lizhuang Ma, Liqing Zhang

Recently, DETR and Deformable DETR have been proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance as previous complex hand-crafted detectors.

Object object-detection +2

Attention-Based 3D Seismic Fault Segmentation Training by a Few 2D Slice Labels

no code implementations9 May 2021 YiMin Dou, Kewen Li, Jianbing Zhu, Xiao Li, Yingjie Xi

The task of image segmentation requires huge labels, especially 3D seismic data, which has a complex structure and lots of noise.

Fault Detection Image Segmentation +2

A Geometric Analysis of Neural Collapse with Unconstrained Features

1 code implementation NeurIPS 2021 Zhihui Zhu, Tianyu Ding, Jinxin Zhou, Xiao Li, Chong You, Jeremias Sulam, Qing Qu

In contrast to existing landscape analysis for deep neural networks which is often disconnected from practice, our analysis of the simplified model not only does it explain what kind of features are learned in the last layer, but it also shows why they can be efficiently optimized in the simplified settings, matching the empirical observations in practical deep network architectures.

Out-of-Step Detection Based On an Improved Line Potential Energy Criterion

no code implementations14 Apr 2021 Xiao Li, Chongru Liu, Jin Ma

The line potential energy in the cutset is used as the criterion for monitoring the generator instability, but the criterion has the following two limitations due to narrowly defined conditions.

Sensing population distribution from satellite imagery via deep learning: model selection, neighboring effect, and systematic biases

no code implementations3 Mar 2021 Xiao Huang, Di Zhu, Fan Zhang, Tao Liu, Xiao Li, Lei Zou

The rapid development of remote sensing techniques provides rich, large-coverage, and high-temporal information of the ground, which can be coupled with the emerging deep learning approaches that enable latent features and hidden geographical patterns to be extracted.

Model Selection

Convolutional Normalization: Improving Deep Convolutional Network Robustness and Training

1 code implementation NeurIPS 2021 Sheng Liu, Xiao Li, Yuexiang Zhai, Chong You, Zhihui Zhu, Carlos Fernandez-Granda, Qing Qu

Furthermore, we show that our ConvNorm can reduce the layerwise spectral norm of the weight matrices and hence improve the Lipschitzness of the network, leading to easier training and improved robustness for deep ConvNets.

Generative Adversarial Network

Provable Boolean Interaction Recovery from Tree Ensemble obtained via Random Forests

no code implementations23 Feb 2021 Merle Behr, Yu Wang, Xiao Li, Bin Yu

Iterative Random Forests (iRF) use a tree ensemble from iteratively modified RF to obtain predictive and stable non-linear or Boolean interactions of features.

Statistics Theory Statistics Theory

Rethinking Natural Adversarial Examples for Classification Models

1 code implementation23 Feb 2021 Xiao Li, Jianmin Li, Ting Dai, Jie Shi, Jun Zhu, Xiaolin Hu

A detection model based on the classification model EfficientNet-B7 achieved a top-1 accuracy of 53. 95%, surpassing previous state-of-the-art classification models trained on ImageNet, suggesting that accurate localization information can significantly boost the performance of classification models on ImageNet-A.

Classification General Classification +2

Stability of scar states in 2D PXP model against random disorders

no code implementations16 Feb 2021 Ke Huang, Yu Wang, Xiao Li

Recently a class of quantum systems exhibiting weak ergodicity breaking has attracted much attention.

Disordered Systems and Neural Networks Statistical Mechanics

Hybrid Beamforming for mmWave MU-MISO Systems Exploiting Multi-agent Deep Reinforcement Learning

no code implementations1 Feb 2021 Qisheng Wang, Xiao Li, Shi Jin, Yijiain Chen

In this letter, we investigate the hybrid beamforming based on deep reinforcement learning (DRL) for millimeter Wave (mmWave) multi-user (MU) multiple-input-single-output (MISO) system.

reinforcement-learning Reinforcement Learning (RL)

Fooling thermal infrared pedestrian detectors in real world using small bulbs

no code implementations20 Jan 2021 Xiaopei Zhu, Xiao Li, Jianmin Li, Zheyao Wang, Xiaolin Hu

By using a combination method, we successfully hide from the visible light and infrared object detection systems at the same time.

Autonomous Driving object-detection +1

TSQA: Tabular Scenario Based Question Answering

1 code implementation14 Jan 2021 Xiao Li, Yawei Sun, Gong Cheng

To solve the task, we extend state-of-the-art MRC methods with TTGen, a novel table-to-text generator.

Machine Reading Comprehension Multiple-choice +2

A Bayesian Nonparametric model for textural pattern heterogeneity

1 code implementation11 Nov 2020 Xiao Li, Michele Guindani, Chaan S. Ng, Brian P. Hobbs

Cancer radiomics is an emerging discipline promising to elucidate lesion phenotypes and tumor heterogeneity through patterns of enhancement, texture, morphology, and shape.

Applications

Integrated Communication and Localization in mmWave Systems

no code implementations28 Sep 2020 Jie Yang, Jing Xu, Xiao Li, Shi Jin, Bo Gao

As the fifth-generation (5G) mobile communication system is being commercialized, extensive studies on the evolution of 5G and sixth-generation mobile communication systems have been conducted.

Multi-Task Neural Model for Agglutinative Language Translation

no code implementations ACL 2020 Yirong Pan, Xiao Li, Yating Yang, Rui Dong

Neural machine translation (NMT) has achieved impressive performance recently by using large-scale parallel corpora.

Decoder Machine Translation +3

Distribution Aligned Multimodal and Multi-Domain Image Stylization

no code implementations2 Jun 2020 Minxuan Lin, Fan Tang, Wei-Ming Dong, Xiao Li, Chongyang Ma, Changsheng Xu

Currently, there are few methods that can perform both multimodal and multi-domain stylization simultaneously.

Diversity Image Stylization

Curating a COVID-19 data repository and forecasting county-level death counts in the United States

1 code implementation16 May 2020 Nick Altieri, Rebecca L. Barter, James Duncan, Raaz Dwivedi, Karl Kumbier, Xiao Li, Robert Netzorg, Briton Park, Chandan Singh, Yan Shuo Tan, Tiffany Tang, Yu Wang, Chao Zhang, Bin Yu

We use this data to develop predictions and corresponding prediction intervals for the short-term trajectory of COVID-19 cumulative death counts at the county-level in the United States up to two weeks ahead.

COVID-19 Tracking Decision Making +2

A Text Reassembling Approach to Natural Language Generation

no code implementations16 May 2020 Xiao Li, Kees Van Deemter, Chenghua Lin

Recent years have seen a number of proposals for performing Natural Language Generation (NLG) based in large part on statistical techniques.

Text Generation

An Early Study on Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety

no code implementations30 Apr 2020 Jing Han, Kun Qian, Meishu Song, Zijiang Yang, Zhao Ren, Shuo Liu, Juan Liu, Huaiyuan Zheng, Wei Ji, Tomoya Koike, Xiao Li, Zixing Zhang, Yoshiharu Yamamoto, Björn W. Schuller

In particular, by analysing speech recordings from these patients, we construct audio-only-based models to automatically categorise the health state of patients from four aspects, including the severity of illness, sleep quality, fatigue, and anxiety.

Sleep Quality

Deep Reinforcement Learning for Adaptive Learning Systems

no code implementations17 Apr 2020 Xiao Li, Hanchen Xu, Jinming Zhang, Hua-hua Chang

In this paper, we formulate the adaptive learning problem---the problem of how to find an individualized learning plan (called policy) that chooses the most appropriate learning materials based on learner's latent traits---faced in adaptive learning systems as a Markov decision process (MDP).

Q-Learning reinforcement-learning +1

COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis

no code implementations24 Mar 2020 Björn W. Schuller, Dagmar M. Schuller, Kun Qian, Juan Liu, Huaiyuan Zheng, Xiao Li

We come to the conclusion that CA appears ready for implementation of (pre-)diagnosis and monitoring tools, and more generally provides rich and significant, yet so far untapped potential in the fight against COVID-19 spread.

Finding the Sparsest Vectors in a Subspace: Theory, Algorithms, and Applications

no code implementations20 Jan 2020 Qing Qu, Zhihui Zhu, Xiao Li, Manolis C. Tsakiris, John Wright, René Vidal

The problem of finding the sparsest vector (direction) in a low dimensional subspace can be considered as a homogeneous variant of the sparse recovery problem, which finds applications in robust subspace recovery, dictionary learning, sparse blind deconvolution, and many other problems in signal processing and machine learning.

Dictionary Learning Representation Learning

Morphological Word Segmentation on Agglutinative Languages for Neural Machine Translation

no code implementations2 Jan 2020 Yirong Pan, Xiao Li, Yating Yang, Rui Dong

Experimental results show that our morphologically motivated word segmentation method is better suitable for the NMT model, which achieves significant improvements on Turkish-English and Uyghur-Chinese machine translation tasks on account of reducing data sparseness and language complexity.

Machine Translation NMT +2

MIMO Transmission through Reconfigurable Intelligent Surface: System Design, Analysis, and Implementation

no code implementations20 Dec 2019 Wankai Tang, Jun Yan Dai, Ming Zheng Chen, Kai-Kit Wong, Xiao Li, Xinsheng Zhao, Shi Jin, Qiang Cheng, Tie Jun Cui

Reconfigurable intelligent surface (RIS) is a new paradigm that has great potential to achieve cost-effective, energy-efficient information modulation for wireless transmission, by the ability to change the reflection coefficients of the unit cells of a programmable metasurface.

Analysis of the Optimization Landscapes for Overcomplete Representation Learning

no code implementations5 Dec 2019 Qing Qu, Yuexiang Zhai, Xiao Li, Yuqian Zhang, Zhihui Zhu

In this work, we show these problems can be formulated as $\ell^4$-norm optimization problems with spherical constraint, and study the geometric properties of their nonconvex optimization landscapes.

Representation Learning

A Stable Variational Autoencoder for Text Modelling

1 code implementation WS 2019 Ruizhe Li, Xiao Li, Chenghua Lin, Matthew Collinson, Rui Mao

Variational Autoencoder (VAE) is a powerful method for learning representations of high-dimensional data.

Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods

1 code implementation12 Nov 2019 Xiao Li, Shixiang Chen, Zengde Deng, Qing Qu, Zhihui Zhu, Anthony Man Cho So

To the best of our knowledge, these are the first convergence guarantees for using Riemannian subgradient-type methods to optimize a class of nonconvex nonsmooth functions over the Stiefel manifold.

Dictionary Learning Vocal Bursts Type Prediction

Physical Layer Security Enhancement Exploiting Intelligent Reflecting Surface

no code implementations7 Nov 2019 Keming Feng, Xiao Li, Yu Han, Shi Jin, Yijian Chen

In this letter, the use of intelligent reflecting surface (IRS) to enhance the physical layer security of downlink wireless communication is investigated.

A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind Deconvolution

1 code implementation NeurIPS 2019 Qing Qu, Xiao Li, Zhihui Zhu

We study the multi-channel sparse blind deconvolution (MCS-BD) problem, whose task is to simultaneously recover a kernel $\mathbf a$ and multiple sparse inputs $\{\mathbf x_i\}_{i=1}^p$ from their circulant convolution $\mathbf y_i = \mathbf a \circledast \mathbf x_i $ ($i=1,\cdots, p$).

Computational Efficiency

PrecoderNet: Hybrid Beamforming for Millimeter Wave Systems with Deep Reinforcement Learning

no code implementations31 Jul 2019 Qisheng Wang, Keming Feng, Xiao Li, Shi Jin

In this letter, we investigate the hybrid beamforming for millimeter wave massive multiple-input multiple-output (MIMO) system based on deep reinforcement learning (DRL).

reinforcement-learning Reinforcement Learning (RL)

Latent Space Factorisation and Manipulation via Matrix Subspace Projection

2 code implementations ICML 2020 Xiao Li, Chenghua Lin, Ruizhe Li, Chaozheng Wang, Frank Guerin

We demonstrate the utility of our method for attribute manipulation in autoencoders trained across varied domains, using both human evaluation and automated methods.

Ranked #7 on Image Generation on CelebA 256x256 (FID metric)

Attribute Face Generation +1

A Debiased MDI Feature Importance Measure for Random Forests

3 code implementations NeurIPS 2019 Xiao Li, Yu Wang, Sumanta Basu, Karl Kumbier, Bin Yu

Based on the original definition of MDI by Breiman et al. for a single tree, we derive a tight non-asymptotic bound on the expected bias of MDI importance of noisy features, showing that deep trees have higher (expected) feature selection bias than shallow ones.

Feature Importance feature selection +1

Synthesizing 3D Shapes from Silhouette Image Collections using Multi-projection Generative Adversarial Networks

no code implementations CVPR 2019 Xiao Li, Yue Dong, Pieter Peers, Xin Tong

Key to our method is a novel multi-projection generative adversarial network (MP-GAN) that trains a 3D shape generator to be consistent with multiple 2D projections of the 3D shapes, and without direct access to these 3D shapes.

Generative Adversarial Network Weakly-supervised Learning

Automata Guided Skill Composition

no code implementations ICLR 2019 Xiao Li, Yao Ma, Calin Belta

Skills learned through (deep) reinforcement learning often generalizes poorly across tasks and re-training is necessary when presented with a new task.

reinforcement-learning Reinforcement Learning (RL)

Arbitrage of Energy Storage in Electricity Markets with Deep Reinforcement Learning

no code implementations28 Apr 2019 Hanchen Xu, Xiao Li, Xiangyu Zhang, Junbo Zhang

In this letter, we address the problem of controlling energy storage systems (ESSs) for arbitrage in real-time electricity markets under price uncertainty.

reinforcement-learning Reinforcement Learning (RL)

Mimicking the In-Camera Color Pipeline for Camera-Aware Object Compositing

no code implementations27 Mar 2019 Jun Gao, Xiao Li, Li-Wei Wang, Sanja Fidler, Stephen Lin

We present a method for compositing virtual objects into a photograph such that the object colors appear to have been processed by the photo's camera imaging pipeline.

Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization

no code implementations NeurIPS 2018 Zhihui Zhu, Xiao Li, Kai Liu, Qiuwei Li

Symmetric nonnegative matrix factorization (NMF), a special but important class of the general NMF, is demonstrated to be useful for data analysis and in particular for various clustering tasks.

Clustering Image Clustering

Statistical NLG for Generating the Content and Form of Referring Expressions

no code implementations WS 2018 Xiao Li, Kees Van Deemter, Chenghua Lin

This paper argues that a new generic approach to statistical NLG can be made to perform Referring Expression Generation (REG) successfully.

Attribute Referring Expression +2

Nonconvex Robust Low-rank Matrix Recovery

no code implementations24 Sep 2018 Xiao Li, Zhihui Zhu, Anthony Man-Cho So, Rene Vidal

In this paper we study the problem of recovering a low-rank matrix from a number of random linear measurements that are corrupted by outliers taking arbitrary values.

Information Theory Information Theory

Automata Guided Reinforcement Learning With Demonstrations

no code implementations17 Sep 2018 Xiao Li, Yao Ma, Calin Belta

Tasks with complex temporal structures and long horizons pose a challenge for reinforcement learning agents due to the difficulty in specifying the tasks in terms of reward functions as well as large variances in the learning signals.

reinforcement-learning Reinforcement Learning (RL)

AUTOMATA GUIDED HIERARCHICAL REINFORCEMENT LEARNING FOR ZERO-SHOT SKILL COMPOSITION

no code implementations ICLR 2018 Xiao Li, Yao Ma, Calin Belta

An obstacle that prevents the wide adoption of (deep) reinforcement learning (RL) in control systems is its need for a large number of interactions with the environment in order to master a skill.

Hierarchical Reinforcement Learning reinforcement-learning +1

Automata-Guided Hierarchical Reinforcement Learning for Skill Composition

no code implementations31 Oct 2017 Xiao Li, Yao Ma, Calin Belta

Skills learned through (deep) reinforcement learning often generalizes poorly across domains and re-training is necessary when presented with a new task.

Hierarchical Reinforcement Learning reinforcement-learning +1

Optimized Structured Sparse Sensing Matrices for Compressive Sensing

no code implementations19 Sep 2017 Tao Hong, Xiao Li, Zhihui Zhu, Qiuwei Li

We consider designing a robust structured sparse sensing matrix consisting of a sparse matrix with a few non-zero entries per row and a dense base matrix for capturing signals efficiently We design the robust structured sparse sensing matrix through minimizing the distance between the Gram matrix of the equivalent dictionary and the target Gram of matrix holding small mutual coherence.

Compressive Sensing Image Compression

Investigating the content and form of referring expressions in Mandarin: introducing the Mtuna corpus

no code implementations WS 2017 Kees van Deemter, Le Sun, Rint Sybesma, Xiao Li, Bo Chen, Muyun Yang

East Asian languages are thought to handle reference differently from languages such as English, particularly in terms of the marking of definiteness and number.

Text Generation

Reinforcement Learning With Temporal Logic Rewards

no code implementations11 Dec 2016 Xiao Li, Cristian-Ioan Vasile, Calin Belta

We propose Truncated Linear Temporal Logic (TLTL) as specifications language, that is arguably well suited for the robotics applications, together with quantitative semantics, i. e., robustness degree.

reinforcement-learning Reinforcement Learning (RL)

A Hierarchical Reinforcement Learning Method for Persistent Time-Sensitive Tasks

no code implementations20 Jun 2016 Xiao Li, Calin Belta

Reinforcement learning has been applied to many interesting problems such as the famous TD-gammon and the inverted helicopter flight.

Hierarchical Reinforcement Learning reinforcement-learning +1

An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching

no code implementations NeurIPS 2015 Xiao Li, Kannan Ramchandran

By writing the cut function as a polynomial and exploiting the graph structure, we propose a sketching algorithm to learn the an arbitrary $n$-node unknown graph using only few cut queries, which scales {\it almost linearly} in the number of edges and {\it sub-linearly} in the graph size $n$.

Active Learning

SPRIGHT: A Fast and Robust Framework for Sparse Walsh-Hadamard Transform

3 code implementations26 Aug 2015 Xiao Li, Joseph K. Bradley, Sameer Pawar, Kannan Ramchandran

We consider the problem of computing the Walsh-Hadamard Transform (WHT) of some $N$-length input vector in the presence of noise, where the $N$-point Walsh spectrum is $K$-sparse with $K = {O}(N^{\delta})$ scaling sub-linearly in the input dimension $N$ for some $0<\delta<1$.

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