1 code implementation • 20 Oct 2024 • Yuan Zhou, Qiuyue Wang, Yuxuan Cai, Huan Yang
Significant advancements have been made in the field of video generation, with the open-source community contributing a wealth of research papers and tools for training high-quality models.
no code implementations • 7 Oct 2024 • Chen Zhang, Huan Hu, Yuan Zhou, Qiyang Cao, Ruochen Liu, Wenya Wei, Elvis S. Liu
To address the challenges of navigation and combat in modern 3D FPS games, we introduce a method that combines navigation mesh (Navmesh) and shooting-rule with deep reinforcement learning (NSRL).
no code implementations • 2 Oct 2024 • Yuan Zhou, Peng Zhang, Mengya Song, Alice Zheng, Yiwen Lu, Zhiheng Liu, Yong Chen, Zhaohan Xi
In this work, we introduce ZODIAC, an LLM-powered framework with cardiologist-level professionalism designed to engage LLMs in cardiological diagnostics.
no code implementations • 29 Aug 2024 • Jiameng Lyu, Jinxing Xie, Shilin Yuan, Yuan Zhou
Our meta-policy is flexible enough to be applied to a general inventory systems framework covering a wide range of inventory management problems with myopic clairvoyant optimal policy.
no code implementations • 17 Jul 2024 • Huiguo He, Huan Yang, Zixi Tuo, Yuan Zhou, Qiuyue Wang, Yuhang Zhang, Zeyu Liu, Wenhao Huang, Hongyang Chao, Jian Yin
DreamStory consists of (1) an LLM acting as a story director and (2) an innovative Multi-Subject consistent Diffusion model (MSD) for generating consistent multi-subject across the images.
no code implementations • 8 Jul 2024 • Xi Chen, Mo Liu, Yining Wang, Yuan Zhou
In this paper, we consider a multi-stage dynamic assortment optimization problem with multi-nomial choice modeling (MNL) under resource knapsack constraints.
no code implementations • 6 Jul 2024 • Jiameng Lyu, Shilin Yuan, Bingkun Zhou, Yuan Zhou
Under the \alpha-global strong convexity condition, we demonstrate that the worst-case regret of any data-driven method is lower bounded by \Omega(\log T/\alpha), which is the first lower bound result that matches the existing upper bound with respect to both parameter \alpha and time horizon T. Along the way, we propose to analyze the SAA regret via a new gradient approximation technique, as well as a new class of smooth inverted-hat-shaped hard problem instances that might be of independent interest for the lower bounds of broader data-driven problems.
1 code implementation • 28 Jun 2024 • Yutong Chen, Hongzuo Xu, Guansong Pang, Hezhe Qiao, Yuan Zhou, Mingsheng Shang
STEN is composed of a sequence Order prediction-based Temporal Normality learning (OTN) module that captures the temporal correlations within sequences, and a Distance prediction-based Spatial Normality learning (DSN) module that learns the relative spatial relations between sequences in a feature space.
no code implementations • 25 Jun 2024 • Lin Liu, Quande Liu, Shengju Qian, Yuan Zhou, Wengang Zhou, Houqiang Li, Lingxi Xie, Qi Tian
Video generation is a challenging yet pivotal task in various industries, such as gaming, e-commerce, and advertising.
1 code implementation • 28 May 2024 • Botao He, Ze Wang, Yuan Zhou, Jingxi Chen, Chahat Deep Singh, Haojia Li, Yuman Gao, Shaojie Shen, Kaiwei Wang, Yanjun Cao, Chao Xu, Yiannis Aloimonos, Fei Gao, Cornelia Fermuller
These event cameras' output is dependent on both motion and texture.
no code implementations • 15 May 2024 • Prashant Kaushal, Manisha R. Ummadi, Gwendolyn M. Jang, Yennifer Delgado, Sara K. Makanani, Sophie F. Blanc, Decan M. Winters, Jiewei Xu, Benjamin Polacco, Yuan Zhou, Erica Stevenson, Manon Eckhardt, Lorena Zuliani-Alvarez, Robyn Kaake, Danielle L. Swaney, Nevan Krogan, Mehdi Bouhaddou
Proteins congregate into complexes to perform fundamental cellular functions.
no code implementations • 13 Apr 2024 • Zishuo Zhao, Zhixuan Fang, Xuechao Wang, Xi Chen, Yuan Zhou
Most concurrent blockchain systems rely heavily on the Proof-of-Work (PoW) or Proof-of-Stake (PoS) mechanisms for decentralized consensus and security assurance.
no code implementations • 17 Mar 2024 • Yuan Zhou, Richang Hong, Yanrong Guo, Lin Liu, Shijie Hao, Hanwang Zhang
In this paper, we propose to tackle Few-Shot Class-Incremental Learning (FSCIL) from a new perspective, i. e., relation disentanglement, which means enhancing FSCIL via disentangling spurious relation between categories.
no code implementations • 28 Feb 2024 • Mingfei Cheng, Yuan Zhou, Xiaofei Xie, Junjie Wang, Guozhu Meng, Kairui Yang
In this paper, we focus on evaluating the decision-making quality of an ADS and propose the first method for detecting non-optimal decision scenarios (NoDSs), where the ADS does not compute optimal paths for AVs.
no code implementations • 1 Feb 2024 • Yuang Zhang, Haonan An, Zhengru Fang, Guowen Xu, Yuan Zhou, Xianhao Chen, Yuguang Fang
Moreover, in the context of collaborative perception, it is important to recognize that not all CAVs contribute valuable data, and some CAV data even have detrimental effects on collaborative perception.
1 code implementation • 17 Nov 2023 • Hong Liu, Yucheng Cai, Yuan Zhou, Zhijian Ou, Yi Huang, Junlan Feng
Inspired by the recently emerging prompt tuning method that performs well on dialog systems, we propose to use the prompt pool method, where we maintain a pool of key-value paired prompts and select prompts from the pool according to the distance between the dialog history and the prompt keys.
no code implementations • 13 Oct 2023 • Harsh Patel, Yuan Zhou, Alexander P Lamb, Shu Wang, Jieliang Luo
By leveraging operational data as a foundation for the agent's actions, we enhance the explainability of the agent's actions, foster more robust recommendations, and minimize error.
1 code implementation • 25 Sep 2023 • Lei Xiang, Yuan Zhou, Haoran Duan, Yang Long
To address these issues, we propose a novel Dual Feature Augmentation Network (DFAN), which comprises two feature augmentation modules, one for visual features and the other for semantic features.
no code implementations • 15 Sep 2023 • Senkang Hu, Zhengru Fang, Haonan An, Guowen Xu, Yuan Zhou, Xianhao Chen, Yuguang Fang
To address these issues, we propose ACC-DA, a channel-aware collaborative perception framework to dynamically adjust the communication graph and minimize the average transmission delay while mitigating the side effects from the data heterogeneity.
no code implementations • 23 Jul 2023 • Qingren Yao, Yuan Zhou, Chang Tang, Wei Xiang
For hyperspectral image change detection (HSI-CD), one key challenge is to reduce band redundancy, as only a few bands are crucial for change detection while other bands may be adverse to it.
no code implementations • 26 May 2023 • Yixin Wan, Yuan Zhou, Xiulian Peng, Kai-Wei Chang, Yan Lu
To begin with, we are among the first to comprehensively investigate mainstream KD techniques on DNS models to resolve the two challenges.
no code implementations • 18 May 2023 • Yuan Zhou, Xin Chen, Yanrong Guo, Shijie Hao, Richang Hong, Qi Tian
Incremental few-shot semantic segmentation (IFSS) aims to incrementally extend a semantic segmentation model to novel classes according to only a few pixel-level annotated data, while preserving its segmentation capability on previously learned base categories.
no code implementations • CVPR 2023 • Yue Gao, Yuan Zhou, Jinglu Wang, Xiao Li, Xiang Ming, Yan Lu
Our method leverages both self-supervised learned landmarks and 3D face model-based landmarks to model the motion.
1 code implementation • 8 Mar 2023 • Cody Hao Yu, Haozheng Fan, Guangtai Huang, Zhen Jia, Yizhi Liu, Jie Wang, Zach Zheng, Yuan Zhou, Haichen Shen, Junru Shao, Mu Li, Yida Wang
In this paper, we present RAF, a deep learning compiler for training.
no code implementations • 25 Feb 2023 • Yuan Zhou, Jing Mei, Yiqin Yu, Tanveer Syeda-Mahmood
Visual Question Answering (VQA) becomes one of the most active research problems in the medical imaging domain.
no code implementations • 25 Feb 2023 • Chengyu Zheng, Yuan Zhou, Xiulian Peng, Yuan Zhang, Yan Lu
Time-variant factors often occur in real-world full-duplex communication applications.
no code implementations • 21 Feb 2023 • Chengyu Zheng, Yuan Zhou, Xiulian Peng, Yuan Zhang, Yan Lu
For real-time speech enhancement (SE) including noise suppression, dereverberation and acoustic echo cancellation, the time-variance of the audio signals becomes a severe challenge.
no code implementations • 15 Oct 2022 • Zihan Zhang, Yuhang Jiang, Yuan Zhou, Xiangyang Ji
Meanwhile, we show that to achieve $\tilde{O}(\mathrm{poly}(S, A, H)\sqrt{K})$ regret, the number of batches is at least $\Omega\left(H/\log_A(K)+ \log_2\log_2(K) \right)$, which matches our upper bound up to logarithmic terms.
no code implementations • 3 Aug 2022 • Wangyang Yue, Yuan Zhou, Xiaochuan Zhang, Yuchen Hua, Zhiyuan Wang, Guang Kou
Various methods, such as domain randomization, have been proposed to deal with such situations by training agents under different environmental setups, and therefore they can be generalized to different environments during deployment.
no code implementations • 22 Jul 2022 • Xi Chen, Jiameng Lyu, Yining Wang, Yuan Zhou
We introduce the regularized revenue, i. e., the total revenue with a balancing regularization, as our objective to incorporate fair resource-consumption balancing into the revenue maximization goal.
no code implementations • 4 May 2022 • Yuan Zhou, Keran Chen, Xiaofeng Li
The location of the sea fog in each image in SFDD is accurately marked.
1 code implementation • ICLR 2022 • Tanmay Gangwani, Yuan Zhou, Jian Peng
In this work, we propose an algorithm that trains an intermediary policy in the learner environment and uses it as a surrogate expert for the learner.
no code implementations • 2 Mar 2022 • Xingshuo Han, Guowen Xu, Yuan Zhou, Xuehuan Yang, Jiwei Li, Tianwei Zhang
However, DNN models are vulnerable to different types of adversarial attacks, which pose significant risks to the security and safety of the vehicles and passengers.
no code implementations • 27 Dec 2021 • Yuan Zhou, Hemant D. Tagare
Classifying SPECT images requires a preprocessing step which normalizes the images using a normalization region.
no code implementations • 2 Dec 2021 • Ziyuan Zhong, Yun Tang, Yuan Zhou, Vania de Oliveira Neves, Yang Liu, Baishakhi Ray
To bridge this gap, in this work, we provide a generic formulation of scenario-based testing in high-fidelity simulation and conduct a literature review on the existing works.
1 code implementation • ICLR 2022 • Zhizhou Ren, Ruihan Guo, Yuan Zhou, Jian Peng
Based on this framework, this paper proposes a novel reward redistribution algorithm, randomized return decomposition (RRD), to learn a proxy reward function for episodic reinforcement learning.
no code implementations • 16 Nov 2021 • Xi Chen, Jiameng Lyu, Xuan Zhang, Yuan Zhou
To handle this general class, we propose a soft fairness constraint and develop a dynamic pricing policy that achieves $\tilde{O}(T^{4/5})$ regret.
no code implementations • 13 Nov 2021 • Yuan Zhou, Haiyang Wang, Shuwei Huo, Boyu Wang
Thus, it is appropriate to consider using NAS methods to discover a better self-attention architecture automatically.
no code implementations • 15 Oct 2021 • Zihan Zhang, Xiangyang Ji, Yuan Zhou
We study the optimal batch-regret tradeoff for batch linear contextual bandits.
no code implementations • 13 Aug 2021 • Chenyu You, Yuan Zhou, Ruihan Zhao, Lawrence Staib, James S. Duncan
However, most existing learning-based approaches usually suffer from limited manually annotated medical data, which poses a major practical problem for accurate and robust medical image segmentation.
no code implementations • 12 Jul 2021 • Yuan Zhou, Yanrong Guo, Shijie Hao, Richang Hong, ZhengJun Zha, Meng Wang
To overcome these problems, we propose a new Global Relatedness Decoupled-Distillation (GRDD) method using the global category knowledge and the Relatedness Decoupled-Distillation (RDD) strategy.
no code implementations • 11 Jul 2021 • Yuanyi Zhong, Yuan Zhou, Jian Peng
The control variates (CV) method is widely used in policy gradient estimation to reduce the variance of the gradient estimators in practice.
no code implementations • 22 Jun 2021 • Beining Han, Zhizhou Ren, Zuofan Wu, Yuan Zhou, Jian Peng
We study deep reinforcement learning (RL) algorithms with delayed rewards.
no code implementations • 5 May 2021 • Yuan Zhou, Yanrong Guo, Shijie Hao, Richang Hong, Jiebo Luo
The challenges of this task are twofold: (i) it is difficult to overcome the impact of data scarcity under the interference of missing views; (ii) the limited number of data exacerbates information scarcity, thus making it harder to address the view-missing issue in turn.
no code implementations • 13 Jan 2021 • Yiqin Yu, Pin-Yu Chen, Yuan Zhou, Jing Mei
With the successful adoption of machine learning on electronic health records (EHRs), numerous computational models have been deployed to address a variety of clinical problems.
1 code implementation • 4 Dec 2020 • Shubham Rai, Walter Lau Neto, Yukio Miyasaka, Xinpei Zhang, Mingfei Yu, Qingyang Yi Masahiro Fujita, Guilherme B. Manske, Matheus F. Pontes, Leomar S. da Rosa Junior, Marilton S. de Aguiar, Paulo F. Butzen, Po-Chun Chien, Yu-Shan Huang, Hoa-Ren Wang, Jie-Hong R. Jiang, Jiaqi Gu, Zheng Zhao, Zixuan Jiang, David Z. Pan, Brunno A. de Abreu, Isac de Souza Campos, Augusto Berndt, Cristina Meinhardt, Jonata T. Carvalho, Mateus Grellert, Sergio Bampi, Aditya Lohana, Akash Kumar, Wei Zeng, Azadeh Davoodi, Rasit O. Topaloglu, Yuan Zhou, Jordan Dotzel, Yichi Zhang, Hanyu Wang, Zhiru Zhang, Valerio Tenace, Pierre-Emmanuel Gaillardon, Alan Mishchenko, Satrajit Chatterjee
If the function is incompletely-specified, the implementation has to be true only on the care set.
no code implementations • NeurIPS 2020 • Zihan Zhang, Yuan Zhou, Xiangyang Ji
We study the reinforcement learning problem in the setting of finite-horizon1episodic Markov Decision Processes (MDPs) with S states, A actions, and episode length H. We propose a model-free algorithm UCB-ADVANTAGE and prove that it achieves \tilde{O}(\sqrt{H^2 SAT}) regret where T=KH and K is the number of episodes to play.
1 code implementation • 5 Nov 2020 • Tanmay Gangwani, Jian Peng, Yuan Zhou
Quality-Diversity (QD) is a concept from Neuroevolution with some intriguing applications to Reinforcement Learning.
2 code implementations • NeurIPS 2020 • Tanmay Gangwani, Yuan Zhou, Jian Peng
To make credit assignment easier, recent works have proposed algorithms to learn dense "guidance" rewards that could be used in place of the sparse or delayed environmental rewards.
no code implementations • 15 Oct 2020 • Yuan Zhou, Xiangrui Li
Then two set of pseudo labels are used to jointly train a student network with the same structure as the teacher.
1 code implementation • 10 Oct 2020 • Yicheng Luo, Antonio Filieri, Yuan Zhou
Probabilistic software analysis aims at quantifying the probability of a target event occurring during the execution of a program processing uncertain incoming data or written itself using probabilistic programming constructs.
1 code implementation • 1 Oct 2020 • David Tolpin, Yuan Zhou, Tom Rainforth, Hongseok Yang
We tackle the problem of conditioning probabilistic programs on distributions of observable variables.
no code implementations • 1 Oct 2020 • David Tolpin, Yuan Zhou, Hongseok Yang
In this work, we cast policy search in stochastic domains as a Bayesian inference problem and provide a scheme for encoding such problems as nested probabilistic programs.
no code implementations • 26 Sep 2020 • Guangyu Xi, Chao Tao, Yuan Zhou
We study MNL bandits, which is a variant of the traditional multi-armed bandit problem, under risk criteria.
no code implementations • 13 Sep 2020 • Yuanyi Zhong, Yuan Zhou, Jian Peng
Reinforcement learning from self-play has recently reported many successes.
no code implementations • 19 Aug 2020 • Yuan Zhou, Mingfei Wang, Ruolin Wang, Shuwei Huo
In this paper, we continue our work on video relocalization task.
no code implementations • 29 Jul 2020 • Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Juntang Zhuang, Pamela Ventola, James S. Duncan
We propose an interpretable GNN framework with a novel salient region selection mechanism to determine neurological brain biomarkers associated with disorders.
no code implementations • 20 Jul 2020 • Yuan Zhou, Mingfei Wang, Ruolin Wang, Shuwei Huo
In this paper, we focus on video relocalization task, which uses a query video clip as input to retrieve a semantic relative video clip in another untrimmed long video.
no code implementations • ICML 2020 • Kefan Dong, Yingkai Li, Qin Zhang, Yuan Zhou
We also present the ESUCB algorithm with item switching cost $O(N \log^2 T)$.
no code implementations • 4 Jul 2020 • Yufei Ruan, Jiaqi Yang, Yuan Zhou
Motivated by practical needs such as large-scale learning, we study the impact of adaptivity constraints to linear contextual bandits, a central problem in online active learning.
no code implementations • 6 Jun 2020 • Zihan Zhang, Yuan Zhou, Xiangyang Ji
In this paper we consider the problem of learning an $\epsilon$-optimal policy for a discounted Markov Decision Process (MDP).
1 code implementation • 22 May 2020 • Shijie Hao, Yuan Zhou, Yanrong Guo, Richang Hong, Jun Cheng, Meng Wang
In SGCPNet, we propose the strategy of spatial-detail guided context propagation.
no code implementations • 13 May 2020 • Xiaojin Zhang, Honglei Zhuang, Shengyu Zhang, Yuan Zhou
We study a variant of the thresholding bandit problem (TBP) in the context of outlier detection, where the objective is to identify the outliers whose rewards are above a threshold.
no code implementations • 21 Apr 2020 • Zihan Zhang, Yuan Zhou, Xiangyang Ji
We study the reinforcement learning problem in the setting of finite-horizon episodic Markov Decision Processes (MDPs) with $S$ states, $A$ actions, and episode length $H$.
no code implementations • 20 Apr 2020 • Nikolai Karpov, Qin Zhang, Yuan Zhou
We give optimal time-round tradeoffs, as well as demonstrate complexity separations between top-$1$ arm identification and top-$m$ arm identifications for general $m$ and between fixed-time and fixed-confidence variants.
no code implementations • 2 Mar 2020 • David Tolpin, Yuan Zhou, Hongseok Yang
Probabilistic programs with mixed support (both continuous and discrete latent random variables) commonly appear in many probabilistic programming systems (PPSs).
no code implementations • 1 Mar 2020 • Yuan Zhou, Dandan Li, Shuwei Huo, Sun-Yuan Kung
At present, the most effective and widely-used activation function is ReLU.
no code implementations • 22 Feb 2020 • Yuan Zhou, Tao Cao, Wei Xiang
As a promising technology in the Internet of Underwater Things, underwater sensor networks have drawn a widespread attention from both academia and industry.
no code implementations • 20 Feb 2020 • Yuan Zhou, Kangming Yan
Owing to refraction, absorption, and scattering of light by suspended particles in water, raw underwater images suffer from low contrast, blurred details, and color distortion.
no code implementations • 24 Nov 2019 • Xukai Xie, Yuan Zhou, Sun-Yuan Kung
All the existing methods determine the importance of each operation directly by architecture weights.
no code implementations • 21 Nov 2019 • Bingyuan Liu, Jiantao Zhang, Xiaoting Zhang, Wei zhang, Chuanhui Yu, Yuan Zhou
However, few works focus on the understanding of furniture within the scenes and a large-scale dataset is also lacked to advance the field.
no code implementations • 4 Nov 2019 • Yuan Zhou, Hongru Li, Sun-Yuan Kung
In the present study, we developed a novel method, referred to as Gemini Network, for effective modeling of temporal structures and achieving high-performance temporal action localization.
no code implementations • 4 Nov 2019 • Yuan Zhou, Xiaoting Du, Yeda Zhang, Sun-Yuan Kung
To this end, we propose the cross-scale residual network to exploit scale-related features and the inter-task correlations among the three tasks.
no code implementations • 1 Nov 2019 • Dandan Li, Yuan Zhou, Shuwei Huo, Sun-Yuan Kung
Convolutional neural networks (CNNs) are inherently suffering from massively redundant computation (FLOPs) due to the dense connection pattern between feature maps and convolution kernels.
no code implementations • ICML 2020 • Yuan Zhou, Hongseok Yang, Yee Whye Teh, Tom Rainforth
Universal probabilistic programming systems (PPSs) provide a powerful framework for specifying rich probabilistic models.
no code implementations • 5 Sep 2019 • Kefan Dong, Jian Peng, Yining Wang, Yuan Zhou
Our learning algorithm, Adaptive Value-function Elimination (AVE), is inspired by the policy elimination algorithm proposed in (Jiang et al., 2017), known as OLIVE.
no code implementations • 7 Aug 2019 • Yuan Zhou, Bingzhang Hu, and Jun He, Yu Guan, Ling Shao
Age synthesis methods typically take a single image as input and use a specific number to control the age of the generated image.
no code implementations • 2 Jul 2019 • Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, James S. Duncan
Our pipeline can be generalized to other graph feature importance interpretation problems.
1 code implementation • NeurIPS 2019 • Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, Jian Peng
Goal-oriented reinforcement learning has recently been a practical framework for robotic manipulation tasks, in which an agent is required to reach a certain goal defined by a function on the state space.
no code implementations • 9 Jun 2019 • Xukai Xie, Yuan Zhou, Sun-Yuan Kung
Using this operation, feature maps of different group cannot communicate, which restricts their representation capability.
no code implementations • NeurIPS 2019 • Chao Tao, Saùl Blanco, Jian Peng, Yuan Zhou
We consider the thresholding bandit problem, whose goal is to find arms of mean rewards above a given threshold $\theta$, with a fixed budget of $T$ trials.
no code implementations • 4 May 2019 • Yingkai Li, Yining Wang, Xi Chen, Yuan Zhou
Linear contextual bandit is an important class of sequential decision making problems with a wide range of applications to recommender systems, online advertising, healthcare, and many other machine learning related tasks.
no code implementations • 5 Apr 2019 • Chao Tao, Qin Zhang, Yuan Zhou
Best arm identification (or, pure exploration) in multi-armed bandits is a fundamental problem in machine learning.
no code implementations • 30 Mar 2019 • Yingkai Li, Yining Wang, Yuan Zhou
We study the linear contextual bandit problem with finite action sets.
1 code implementation • 6 Mar 2019 • Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood
We develop a new Low-level, First-order Probabilistic Programming Language (LF-PPL) suited for models containing a mix of continuous, discrete, and/or piecewise-continuous variables.
no code implementations • 14 Dec 2018 • Xiaoxiao Li, Nicha C. Dvornek, Yuan Zhou, Juntang Zhuang, Pamela Ventola, James S. Duncan
Cooperative game theory is advantageous here because it directly considers the interaction between features and can be applied to any machine learning method, making it a novel, more accurate way of determining instance-wise biomarker importance from deep learning models.
no code implementations • NeurIPS 2018 • Yining Wang, Xi Chen, Yuan Zhou
In this paper we consider the dynamic assortment selection problem under an uncapacitated multinomial-logit (MNL) model.
no code implementations • 31 Oct 2018 • Xiaoyu Lu, Tom Rainforth, Yuan Zhou, Jan-Willem van de Meent, Yee Whye Teh
We study adaptive importance sampling (AIS) as an online learning problem and argue for the importance of the trade-off between exploration and exploitation in this adaptation.
no code implementations • 31 Oct 2018 • Xi Chen, Yining Wang, Yuan Zhou
To this end, we develop an upper confidence bound (UCB) based policy and establish the regret bound on the order of $\widetilde O(d\sqrt{T})$, where $d$ is the dimension of the feature and $\widetilde O$ suppresses logarithmic dependence.
no code implementations • ICLR 2019 • Yuan Xie, Boyi Liu, Qiang Liu, Zhaoran Wang, Yuan Zhou, Jian Peng
Such an error reduction phenomenon is somewhat surprising as the estimated surrogate policy is less accurate than the given historical policy.
no code implementations • ICML 2018 • Chao Tao, Saúl Blanco, Yuan Zhou
We study the best arm identification problem in linear bandits, where the mean reward of each arm depends linearly on an unknown $d$-dimensional parameter vector $\theta$, and the goal is to identify the arm with the largest expected reward.
no code implementations • 27 Jun 2018 • Xi Chen, Chao Shi, Yining Wang, Yuan Zhou
One key challenge is that utilities of products are unknown to the seller and need to be learned.
no code implementations • 25 Jun 2018 • Tom Rainforth, Yuan Zhou, Xiaoyu Lu, Yee Whye Teh, Frank Wood, Hongseok Yang, Jan-Willem van de Meent
We introduce inference trees (ITs), a new class of inference methods that build on ideas from Monte Carlo tree search to perform adaptive sampling in a manner that balances exploration with exploitation, ensures consistency, and alleviates pathologies in existing adaptive methods.
1 code implementation • NeurIPS 2019 • Weizhe Hua, Yuan Zhou, Christopher De Sa, Zhiru Zhang, G. Edward Suh
Combining our method with knowledge distillation reduces the compute cost of ResNet-18 by 2. 6$\times$ without accuracy drop on ImageNet.
no code implementations • NeurIPS 2018 • Jiecao Chen, Qin Zhang, Yuan Zhou
We study the collaborative PAC learning problem recently proposed in Blum et al.~\cite{BHPQ17}, in which we have $k$ players and they want to learn a target function collaboratively, such that the learned function approximates the target function well on all players' distributions simultaneously.
no code implementations • NeurIPS 2018 • Xi Chen, Yining Wang, Yuan Zhou
We further establish the matching lower bound result to show the optimality of our policy.
1 code implementation • 7 Apr 2018 • Bradley Gram-Hansen, Yuan Zhou, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood
Hamiltonian Monte Carlo (HMC) is arguably the dominant statistical inference algorithm used in most popular "first-order differentiable" Probabilistic Programming Languages (PPLs).
no code implementations • 25 Jan 2018 • Yuan Zhou, Erin B. Wetherley, Paul D. Gader
Spectral libraries were built by manually identifying and extracting pure spectra from both resolution images, resulting in 3, 287 spectra at 16 m and 15, 426 spectra at 4 m. We then unmixed ROIs of each resolution using the following unmixing algorithms: the set-based algorithms MESMA and AAM, and the distribution-based algorithms GMM, NCM, and BCM.
1 code implementation • 29 Sep 2017 • Yuan Zhou, Anand Rangarajan, Paul D. Gader
We show, given the GMM starting premise, that the distribution of the mixed pixel (under the linear mixing model) is also a GMM (and this is shown from two perspectives).
no code implementations • ICML 2017 • Jiecao Chen, Xi Chen, Qin Zhang, Yuan Zhou
We study the problem of selecting $K$ arms with the highest expected rewards in a stochastic $n$-armed bandit game.
no code implementations • 30 Sep 2015 • Yuan Zhou, Anand Rangarajan, Paul Gader
In this paper, we show that NCM can be used for calculating the uncertainty of the estimated endmembers with spatial priors incorporated for better unmixing.