no code implementations • 17 Mar 2025 • Yu Xia, Zhiqiang Xu
This paper investigates the ability of finite samples to identify two-layer irreducible shallow networks with various nonlinear activation functions, including rectified linear units (ReLU) and analytic functions such as the logistic sigmoid and hyperbolic tangent.
no code implementations • 17 Mar 2025 • Shitong Shao, Hongwei Yi, Hanzhong Guo, Tian Ye, Daquan Zhou, Michael Lingelbach, Zhiqiang Xu, Zeke Xie
To address these challenges, we propose MagicDistillation, a novel framework designed to reduce inference overhead while ensuring the generalization of VDMs for portrait video synthesis.
no code implementations • 21 Feb 2025 • Xueran Han, YuHan Liu, Mingzhe Li, Wei Liu, Sen Hu, Rui Yan, Zhiqiang Xu, Xiuying Chen
Great novels create immersive worlds with rich character arcs, well-structured plots, and nuanced writing styles.
1 code implementation • 12 Feb 2025 • Dezhong Yao, Yuexin Shi, Tongtong Liu, Zhiqiang Xu
One-shot FL has emerged as a promising approach to mitigate communication overhead, and model-heterogeneous FL solves the problem of diverse computing resources across clients.
1 code implementation • 11 Feb 2025 • Chengqian Gao, Haonan Li, Liu Liu, Zeke Xie, Peilin Zhao, Zhiqiang Xu
Challenging this, we propose a new principle: Preference data vary in difficulty, and overly difficult examples hinder alignment, by exceeding the model's capacity.
no code implementations • 17 Dec 2024 • Zipeng Qi, Buhua Liu, Shiyan Zhang, Bao Li, Zhiqiang Xu, Haoyi Xiong, Zeke Xie
While recent zero-shot diffusion-based classifiers have made performance advancement on benchmark datasets, they still suffered badly from extremely slow classification speed (e. g., ~1000 seconds per classifying single image on ImageNet).
1 code implementation • 14 Dec 2024 • Lichen Bai, Shitong Shao, Zikai Zhou, Zipeng Qi, Zhiqiang Xu, Haoyi Xiong, Zeke Xie
Diffusion models, the most popular generative paradigm so far, can inject conditional information into the generation path to guide the latent towards desired directions.
no code implementations • 25 Nov 2024 • Congliang Chen, Li Shen, Zhiqiang Xu, Wei Liu, Zhi-Quan Luo, Peilin Zhao
We conduct a convergence analysis for a carefully chosen step size to maintain stability.
2 code implementations • 16 Nov 2024 • Shitong Shao, Zikai Zhou, Tian Ye, Lichen Bai, Zhiqiang Xu, Zeke Xie
Text-to-image diffusion models (DMs) develop at an unprecedented pace, supported by thorough theoretical exploration and empirical analysis.
1 code implementation • 14 Nov 2024 • Zikai Zhou, Shitong Shao, Lichen Bai, Zhiqiang Xu, Bo Han, Zeke Xie
With the prepared NPD as the training dataset, we trained a small \textit{noise prompt network}~(NPNet) that can directly learn to transform a random noise into a golden noise.
1 code implementation • 9 Nov 2024 • Ruiyu Li, Peilin Zhao, Guangxia Li, Zhiqiang Xu, XueWei Li
In a classical distributed computing architecture with a central server, the proposed OMTL algorithm with the ADMM optimizer outperforms SGD-based approaches in terms of accuracy and efficiency.
no code implementations • 5 Nov 2024 • Wei Huang, Andi Han, Yongqiang Chen, Yuan Cao, Zhiqiang Xu, Taiji Suzuki
Our analysis provides a unified framework that can characterize the optimization and generalization of both single-modal and multi-modal contrastive learning.
no code implementations • 22 Oct 2024 • Yanjun Chen, Xinming Zhang, Xianghui Wang, Zhiqiang Xu, Xiaoyu Shen, Wei zhang
The Soft Actor-Critic (SAC) algorithm is known for its stability and high sample efficiency in deep reinforcement learning.
1 code implementation • 9 Oct 2024 • Jian Chen, Ruiyi Zhang, Yufan Zhou, Jennifer Healey, Jiuxiang Gu, Zhiqiang Xu, Changyou Chen
Automatic generation of graphical layouts is crucial for many real-world applications, including designing posters, flyers, advertisements, and graphical user interfaces.
no code implementations • 28 Sep 2024 • Haowei Zhang, Jianzhe Liu, Zhen Han, Shuo Chen, Bailan He, Volker Tresp, Zhiqiang Xu, Jindong Gu
The finetuning pipeline consists of our proposed dataset and a training objective for selective decomposition.
1 code implementation • 11 Sep 2024 • Buhua Liu, Shitong Shao, Bao Li, Lichen Bai, Zhiqiang Xu, Haoyi Xiong, James Kwok, Sumi Helal, Zeke Xie
Diffusion models have emerged as the leading paradigm in generative modeling, excelling in various applications.
no code implementations • 10 Sep 2024 • Siqing Li, Jin-Duk Park, Wei Huang, Xin Cao, Won-Yong Shin, Zhiqiang Xu
Heterogeneous graph neural networks (HGNNs) have significantly propelled the information retrieval (IR) field.
no code implementations • 18 Jun 2024 • Egor Ershov, Artyom Panshin, Oleg Karasev, Sergey Korchagin, Shepelev Lev, Alexandr Startsev, Daniil Vladimirov, Ekaterina Zaychenkova, Nikola Banić, Dmitrii Iarchuk, Maria Efimova, Radu Timofte, Arseniy Terekhin, Shuwei Yue, Yuyang Liu, Minchen Wei, Lu Xu, Chao Zhang, Yasi Wang, Furkan Kınlı, Doğa Yılmaz, Barış Özcan, Furkan Kıraç, Shuai Liu, Jingyuan Xiao, Chaoyu Feng, Hao Wang, Guangqi Shao, Yuqian Zhang, Yibin Huang, Wei Luo, Liming Wang, Xiaotao Wang, Lei Lei, Simone Zini, Claudio Rota, Marco Buzzelli, Simone Bianco, Raimondo Schettini, Jin Guo, Tianli Liu, Mohao Wu, Ben Shao, Qirui Yang, Xianghui Li, Qihua Cheng, Fangpu Zhang, Zhiqiang Xu, Jingyu Yang, Huanjing Yue
The top ranking participants' solutions effectively represent the state-of-the-art in nighttime photography rendering.
1 code implementation • 7 Jun 2024 • Cong Zeng, Shengkun Tang, Xianjun Yang, Yuanzhou Chen, Yiyou Sun, Zhiqiang Xu, Yao Li, Haifeng Chen, Wei Cheng, Dongkuan Xu
However, these methods grapple with the misalignment between the distributions of the surrogate and the often undisclosed target models, leading to performance degradation, particularly with the introduction of new, closed-source models.
no code implementations • 6 Jun 2024 • Dake Bu, Wei Huang, Taiji Suzuki, Ji Cheng, Qingfu Zhang, Zhiqiang Xu, Hau-San Wong
We further prove that this shared principle is the key to their success-achieve small test error within a small labeled set.
no code implementations • 30 May 2024 • Zhicheng Chen, Xi Xiao, Ke Xu, Zhong Zhang, Yu Rong, Qing Li, Guojun Gan, Zhiqiang Xu, Peilin Zhao
Multivariate time series prediction is widely used in daily life, which poses significant challenges due to the complex correlations that exist at multi-grained levels.
1 code implementation • 23 May 2024 • Dezhong Yao, Sanmu Li, Yutong Dai, Zhiqiang Xu, Shengshan Hu, Peilin Zhao, Lichao Sun
Federated continual learning (FCL) has received increasing attention due to its potential in handling real-world streaming data, characterized by evolving data distributions and varying client classes over time.
1 code implementation • 2 May 2024 • Chengqian Gao, William de Vazelhes, Hualin Zhang, Bin Gu, Zhiqiang Xu
Evolution Strategies (ES) have emerged as a competitive alternative for model-free reinforcement learning, showcasing exemplary performance in tasks like Mujoco and Atari.
no code implementations • 30 Apr 2024 • Yuekun Dai, Dafeng Zhang, Xiaoming Li, Zongsheng Yue, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Peiqing Yang, Zhezhu Jin, Guanqun Liu, Chen Change Loy, Lize Zhang, Shuai Liu, Chaoyu Feng, Luyang Wang, Shuan Chen, Guangqi Shao, Xiaotao Wang, Lei Lei, Qirui Yang, Qihua Cheng, Zhiqiang Xu, Yihao Liu, Huanjing Yue, Jingyu Yang, Florin-Alexandru Vasluianu, Zongwei Wu, George Ciubotariu, Radu Timofte, Zhao Zhang, Suiyi Zhao, Bo wang, Zhichao Zuo, Yanyan Wei, Kuppa Sai Sri Teja, Jayakar Reddy A, Girish Rongali, Kaushik Mitra, Zhihao Ma, Yongxu Liu, Wanying Zhang, Wei Shang, Yuhong He, Long Peng, Zhongxin Yu, Shaofei Luo, Jian Wang, Yuqi Miao, Baiang Li, Gang Wei, Rakshank Verma, Ritik Maheshwari, Rahul Tekchandani, Praful Hambarde, Satya Narayan Tazi, Santosh Kumar Vipparthi, Subrahmanyam Murala, Haopeng Zhang, Yingli Hou, Mingde Yao, Levin M S, Aniruth Sundararajan, Hari Kumar A
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
1 code implementation • 7 Feb 2024 • Jian Chen, Ruiyi Zhang, Yufan Zhou, Rajiv Jain, Zhiqiang Xu, Ryan Rossi, Changyou Chen
Controllable layout generation refers to the process of creating a plausible visual arrangement of elements within a graphic design (e. g., document and web designs) with constraints representing design intentions.
no code implementations • 27 Dec 2023 • Minbo Ma, Jilin Hu, Christian S. Jensen, Fei Teng, Peng Han, Zhiqiang Xu, Tianrui Li
Spatio-temporal forecasting of future values of spatially correlated time series is important across many cyber-physical systems (CPS).
no code implementations • 18 Nov 2023 • Varun Khurana, Yaman K Singla, Jayakumar Subramanian, Rajiv Ratn Shah, Changyou Chen, Zhiqiang Xu, Balaji Krishnamurthy
We show that BoigLLM outperforms 13x larger models such as GPT-3. 5 and GPT-4 in this task, demonstrating that while these state-of-the-art models can understand images, they lack information on how these images perform in the real world.
no code implementations • 30 Jul 2023 • Peng Tang, Zhiqiang Xu, Pengfei Wei, Xiaobin Hu, Peilin Zhao, Xin Cao, Chunlai Zhou, Tobias Lasser
To further alleviate the contingent effect of recursive stacking, i. e., ringing artifacts, we add identity shortcuts between atrous convolutions to simulate residual deconvolutions.
no code implementations • 8 Jun 2023 • Guanhua Fang, Gennady Samorodnitsky, Zhiqiang Xu
In this work, we stand on a theoretical perspective and show that the negative feedback strategy (a count-based exploration method) is better than the naive random walk search.
1 code implementation • NeurIPS 2023 • Jian Chen, Ruiyi Zhang, Tong Yu, Rohan Sharma, Zhiqiang Xu, Tong Sun, Changyou Chen
Remarkably, by incorporating conditional information from the powerful CLIP model, our method can boost the current SOTA accuracy by 10-20 absolute points in many cases.
Ranked #1 on
Image Classification
on Food-101N
(using extra training data)
1 code implementation • 19 Oct 2022 • Chengqian Gao, Ke Xu, Liu Liu, Deheng Ye, Peilin Zhao, Zhiqiang Xu
A promising paradigm for offline reinforcement learning (RL) is to constrain the learned policy to stay close to the dataset behaviors, known as policy constraint offline RL.
no code implementations • 13 Sep 2022 • Meng Huang, Zhiqiang Xu
Fourier phase retrieval, which seeks to reconstruct a signal from its Fourier magnitude, is of fundamental importance in fields of engineering and science.
1 code implementation • NeurIPS 2023 • Pengfei Wei, Lingdong Kong, Xinghua Qu, Yi Ren, Zhiqiang Xu, Jing Jiang, Xiang Yin
Specifically, we consider the generation of cross-domain videos from two sets of latent factors, one encoding the static information and another encoding the dynamic information.
no code implementations • NeurIPS 2021 • Zhiqiang Xu, Ping Li
We further give the first worst-case analysis that achieves a rate of convergence at $O(\frac{1}{\epsilon}\log\frac{1}{\epsilon})$.
no code implementations • 29 Sep 2021 • Zhuozhuo Tu, Zhiqiang Xu, Tairan Huang, DaCheng Tao, Ping Li
Federated Learning is a machine learning technique where a network of clients collaborates with a server to learn a centralized model while keeping data localized.
no code implementations • NeurIPS 2020 • Yingxue Zhou, Belhal Karimi, Jinxing Yu, Zhiqiang Xu, Ping Li
Adaptive gradient methods such as AdaGrad, RMSprop and Adam have been optimizers of choice for deep learning due to their fast training speed.
1 code implementation • NeurIPS 2023 • Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, Masashi Sugiyama
Weight decay is a simple yet powerful regularization technique that has been very widely used in training of deep neural networks (DNNs).
no code implementations • NeurIPS 2019 • Zhiqiang Xu, Ping Li
To promote the practical use of ALS for CCA, we propose truly alternating least-squares.
no code implementations • NeurIPS 2018 • Zhiqiang Xu
Shift-and-invert preconditioning, as a classic acceleration technique for the leading eigenvector computation, has received much attention again recently, owing to fast least-squares solvers for efficiently approximating matrix inversions in power iterations.
no code implementations • 26 May 2016 • Zhiqiang Xu, Yiping Ke
We generalize it to Riemannian manifolds and realize it to solve the non-convex eigen-decomposition problem.
no code implementations • 19 Oct 2012 • Zhiqiang Xu
In particular, for $M=s^a$ with $a\in [0, 1/2]$, OMMP(M) can recover slowly-decaying $s$-sparse signal within $O(s^{1-a})$ iterations.