1 code implementation • NeurIPS 2023 • Yunkai Gao, Rui Zhang, Jiaming Guo, Fan Wu, Qi Yi, Shaohui Peng, Siming Lan, Ruizhi Chen, Zidong Du, Xing Hu, Qi Guo, Ling Li, Yunji Chen
In this paper, we propose a novel approach called Context Shift Reduction for OMRL (CSRO) to address the context shift problem with only offline datasets.
1 code implementation • 2 Nov 2023 • Yaochen Zhu, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
Recently, there is a growing interest in developing next-generation recommender systems (RSs) based on pretrained large language models (LLMs), fully utilizing their encoded knowledge and reasoning ability.
no code implementations • 4 Sep 2023 • Shaohui Peng, Xing Hu, Qi Yi, Rui Zhang, Jiaming Guo, Di Huang, Zikang Tian, Ruizhi Chen, Zidong Du, Qi Guo, Yunji Chen, Ling Li
Large language models (LLMs) show their powerful automatic reasoning and planning capability with a wealth of semantic knowledge about the human world.
1 code implementation • 16 Jul 2023 • Dean Hazineh, Soon Wei Daniel Lim, Qi Guo, Federico Capasso, Todd Zickler
In contrast to previous work on incoherent opto-electronic filtering that can realize only one spatial filter, our approach can realize a continuous family of filters from a single capture, with filters being selected from the family by adjusting the post-capture digital summation weights.
1 code implementation • 21 Jun 2023 • Shuyao Cheng, Pengwei Jin, Qi Guo, Zidong Du, Rui Zhang, Yunhao Tian, Xing Hu, Yongwei Zhao, Yifan Hao, Xiangtao Guan, Husheng Han, Zhengyue Zhao, Ximing Liu, Ling Li, Xishan Zhang, Yuejie Chu, Weilong Mao, Tianshi Chen, Yunji Chen
By efficiently exploring a search space of unprecedented size 10^{10^{540}}, which is the largest one of all machine-designed objects to our best knowledge, and thus pushing the limits of machine design, our approach generates an industrial-scale RISC-V CPU within only 5 hours.
1 code implementation • 12 Jun 2023 • Qi Yi, Rui Zhang, Shaohui Peng, Jiaming Guo, Yunkai Gao, Kaizhao Yuan, Ruizhi Chen, Siming Lan, Xing Hu, Zidong Du, Xishan Zhang, Qi Guo, Yunji Chen
Domain adaptation in reinforcement learning (RL) mainly deals with the changes of observation when transferring the policy to a new environment.
1 code implementation • 5 Jun 2023 • Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
But since sensitive features may also affect user interests in a fair manner (e. g., race on culture-based preferences), indiscriminately eliminating all the influences of sensitive features inevitably degenerate the recommendations quality and necessary diversities.
1 code implementation • 3 Jun 2023 • Pucheng Dang, Xing Hu, Kaidi Xu, Jinhao Duan, Di Huang, Husheng Han, Rui Zhang, Zidong Du, Qi Guo, Yunji Chen
Unlearning techniques are proposed to prevent third parties from exploiting unauthorized data, which generate unlearnable samples by adding imperceptible perturbations to data for public publishing.
no code implementations • 2 Jun 2023 • Zhengyue Zhao, Jinhao Duan, Xing Hu, Kaidi Xu, Chenan Wang, Rui Zhang, Zidong Du, Qi Guo, Yunji Chen
This imperceptible protective noise makes the data almost unlearnable for diffusion models, i. e., diffusion models trained or fine-tuned on the protected data cannot generate high-quality and diverse images related to the protected training data.
1 code implementation • NeurIPS 2023 • Di Huang, Ziyuan Nan, Xing Hu, Pengwei Jin, Shaohui Peng, Yuanbo Wen, Rui Zhang, Zidong Du, Qi Guo, Yewen Pu, Yunji Chen
We deploy ANPL on the Abstraction and Reasoning Corpus (ARC), a set of unique tasks that are challenging for state-of-the-art AI systems, showing it outperforms baseline programming systems that (a) without the ability to decompose tasks interactively and (b) without the guarantee that the modules can be correctly composed together.
Ranked #4 on
Code Generation
on HumanEval
no code implementations • 9 Mar 2023 • Shaohui Peng, Xing Hu, Rui Zhang, Jiaming Guo, Qi Yi, Ruizhi Chen, Zidong Du, Ling Li, Qi Guo, Yunji Chen
Recently, the language-conditioned policy is proposed to facilitate policy transfer through learning the joint representation of observation and text that catches the compact and invariant information across environments.
no code implementations • 28 Feb 2023 • Chang Liu, Rui Zhang, Xishan Zhang, Yifan Hao, Zidong Du, Xing Hu, Ling Li, Qi Guo
The energy-efficient works try to decrease the precision of multiplication or replace the multiplication with energy-efficient operations such as addition or bitwise shift, to reduce the energy consumption of FP32 multiplications.
no code implementations • 21 Feb 2023 • Pengwei Jin, Di Huang, Rui Zhang, Xing Hu, Ziyuan Nan, Zidong Du, Qi Guo, Yunji Chen
Symbolic regression, the task of extracting mathematical expressions from the observed data $\{ \vx_i, y_i \}$, plays a crucial role in scientific discovery.
no code implementations • 5 Feb 2023 • Ilia Markov, Adrian Vladu, Qi Guo, Dan Alistarh
Communication-reduction techniques are a popular way to improve scalability in data-parallel training of deep neural networks (DNNs).
no code implementations • 16 Nov 2022 • Qi Guo, Yong Qi, Saiyu Qi, Di wu
To our knowledge, we are the first to present an FSSL method that utilizes only 10\% labeled clients, while still achieving superior performance compared to standard federated supervised learning, which uses all clients with labeled data.
no code implementations • 11 Nov 2022 • Ahmad Bin Rabiah, Qi Guo
Conventional image signal processing (ISP) frameworks are designed to reconstruct an RGB image from a single raw measurement.
no code implementations • 13 Oct 2022 • Shaohui Peng, Xing Hu, Rui Zhang, Ke Tang, Jiaming Guo, Qi Yi, Ruizhi Chen, Xishan Zhang, Zidong Du, Ling Li, Qi Guo, Yunji Chen
To address this issue, we propose CDHRL, a causality-driven hierarchical reinforcement learning framework, leveraging a causality-driven discovery instead of a randomness-driven exploration to effectively build high-quality hierarchical structures in complicated environments.
Hierarchical Reinforcement Learning
reinforcement-learning
+1
no code implementations • 13 Oct 2022 • Qi Yi, Rui Zhang, Shaohui Peng, Jiaming Guo, Xing Hu, Zidong Du, Xishan Zhang, Qi Guo, Yunji Chen
Object-oriented reinforcement learning (OORL) is a promising way to improve the sample efficiency and generalization ability over standard RL.
no code implementations • 15 Sep 2022 • Qi Guo, Anatoliy Swishchuk, Bruno Rémillard
In this paper, we consider pricing of European options and spread options for Hawkes-based model for the limit order book.
no code implementations • 26 Aug 2022 • Qinyi Zhu, Liang Wu, Qi Guo, Liangjie Hong
Introducing a brand new workplace type naturally leads to the cold-start problem, which is particularly more common for less active job seekers.
no code implementations • 23 Aug 2022 • Qi Guo, Yong Qi, Saiyu Qi, Di wu, Qian Li
Federated learning (FL) facilitates multiple clients to jointly train a machine learning model without sharing their private data.
no code implementations • 19 Aug 2022 • Husheng Han, Xing Hu, Kaidi Xu, Pucheng Dang, Ying Wang, Yongwei Zhao, Zidong Du, Qi Guo, Yanzhi Yang, Tianshi Chen
This work proposes Themis, a software/hardware system to defend against adversarial patches for real-time robust video object detection.
no code implementations • ICLR 2022 • Di Huang, Rui Zhang, Xing Hu, Xishan Zhang, Pengwei Jin, Nan Li, Zidong Du, Qi Guo, Yunji Chen
In this work, we propose a query-based framework that trains a query neural network to generate informative input-output examples automatically and interactively from a large query space.
no code implementations • NeurIPS 2021 • Husheng Han, Kaidi Xu, Xing Hu, Xiaobing Chen, Ling Liang, Zidong Du, Qi Guo, Yanzhi Wang, Yunji Chen
Our experimental results show that the certified accuracy is increased from 36. 3% (the state-of-the-art certified detection) to 60. 4% on the ImageNet dataset, largely pushing the certified defenses for practical use.
no code implementations • 29 Sep 2021 • Qi Yi, Jiaming Guo, Rui Zhang, Shaohui Peng, Xing Hu, Xishan Zhang, Ke Tang, Zidong Du, Qi Guo, Yunji Chen
Deep Reinforcement Learning (deep RL) has been successfully applied to solve various decision-making problems in recent years.
no code implementations • 4 Sep 2021 • Ruizhi Chen, Xiaoyu Wu, Yansong Pan, Kaizhao Yuan, Ling Li, TianYun Ma, JiYuan Liang, Rui Zhang, Kai Wang, Chen Zhang, Shaohui Peng, Xishan Zhang, Zidong Du, Qi Guo, Yunji Chen
In this framework, the environment can be easily configured to realize all kinds of RL tasks in the mainstream research.
1 code implementation • 26 Jul 2021 • Jiaming Guo, Rui Zhang, Xishan Zhang, Shaohui Peng, Qi Yi, Zidong Du, Xing Hu, Qi Guo, Yunji Chen
In this paper, we propose to replace the state value function with a novel hindsight value function, which leverages the information from the future to reduce the variance of the gradient estimate for stochastic dynamic environments.
4 code implementations • 26 Apr 2021 • Wei Zeng, Xiaozhe Ren, Teng Su, Hui Wang, Yi Liao, Zhiwei Wang, Xin Jiang, ZhenZhang Yang, Kaisheng Wang, Xiaoda Zhang, Chen Li, Ziyan Gong, Yifan Yao, Xinjing Huang, Jun Wang, Jianfeng Yu, Qi Guo, Yue Yu, Yan Zhang, Jin Wang, Hengtao Tao, Dasen Yan, Zexuan Yi, Fang Peng, Fangqing Jiang, Han Zhang, Lingfeng Deng, Yehong Zhang, Zhe Lin, Chao Zhang, Shaojie Zhang, Mingyue Guo, Shanzhi Gu, Gaojun Fan, YaoWei Wang, Xuefeng Jin, Qun Liu, Yonghong Tian
To enhance the generalization ability of PanGu-$\alpha$, we collect 1. 1TB high-quality Chinese data from a wide range of domains to pretrain the model.
Ranked #1 on
Reading Comprehension (Zero-Shot)
on CMRC 2018
Cloze (multi-choices) (Few-Shot)
Cloze (multi-choices) (One-Shot)
+18
no code implementations • 30 Oct 2020 • Nathan Ng, Marzyeh Ghassemi, Narendran Thangarajan, Jiacheng Pan, Qi Guo
In ablations on DBDC4 data from 2019, our semi-supervised learning methods improve the performance of a baseline BERT model by 2\% accuracy.
1 code implementation • 6 Aug 2020 • Weiwei Guo, Xiao-Wei Liu, Sida Wang, Huiji Gao, Ananth Sankar, Zimeng Yang, Qi Guo, Liang Zhang, Bo Long, Bee-Chung Chen, Deepak Agarwal
Ranking is the most important component in a search system.
no code implementations • 19 May 2020 • Xixi Xu, Chao Lu, Liang Zhu, xiangyang xue, Guanxian Chen, Qi Guo, Yining Lin, Zhijian Zhao
Most modern Multi-Object Tracking (MOT) systems typically apply REID-based paradigm to hold a balance between computational efficiency and performance.
1 code implementation • 2020 IEEE 36th International Conference on Data Engineering (ICDE) 2020 • Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu
Predicting Origin-Destination (OD) flow is a crucial problem for intelligent transportation.
no code implementations • 3 Feb 2020 • Di Huang, Xishan Zhang, Rui Zhang, Tian Zhi, Deyuan He, Jiaming Guo, Chang Liu, Qi Guo, Zidong Du, Shaoli Liu, Tianshi Chen, Yunji Chen
In this paper, we propose a novel Decomposable Winograd Method (DWM), which breaks through the limitation of original Winograd's minimal filtering algorithm to a wide and general convolutions.
no code implementations • 1 Nov 2019 • Xishan Zhang, Shaoli Liu, Rui Zhang, Chang Liu, Di Huang, Shiyi Zhou, Jiaming Guo, Yu Kang, Qi Guo, Zidong Du, Yunji Chen
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers.
no code implementations • 18 Sep 2018 • Sahin Cem Geyik, Qi Guo, Bo Hu, Cagri Ozcaglar, Ketan Thakkar, Xianren Wu, Krishnaram Kenthapadi
LinkedIn Talent Solutions business contributes to around 65% of LinkedIn's annual revenue, and provides tools for job providers to reach out to potential candidates and for job seekers to find suitable career opportunities.
no code implementations • 17 Sep 2018 • Rohan Ramanath, Hakan Inan, Gungor Polatkan, Bo Hu, Qi Guo, Cagri Ozcaglar, Xianren Wu, Krishnaram Kenthapadi, Sahin Cem Geyik
In this paper, we present the results of our application of deep and representation learning models on LinkedIn Recruiter.
no code implementations • ECCV 2018 • Qi Guo, Iuri Frosio, Orazio Gallo, Todd Zickler, Jan Kautz
Scene motion, multiple reflections, and sensor noise introduce artifacts in the depth reconstruction performed by time-of-flight cameras.
no code implementations • 23 Oct 2017 • Jinhua Tao, Zidong Du, Qi Guo, Huiying Lan, Lei Zhang, Shengyuan Zhou, Lingjie Xu, Cong Liu, Haifeng Liu, Shan Tang, Allen Rush, Willian Chen, Shaoli Liu, Yunji Chen, Tianshi Chen
The variety of emerging intelligence processors requires standard benchmarks for fair comparison and system optimization (in both software and hardware).
no code implementations • ICCV 2017 • Qi Guo, Emma Alexander, Todd Zickler
The focal track sensor is a monocular and computationally efficient depth sensor that is based on defocus controlled by a liquid membrane lens.
no code implementations • 29 Mar 2017 • Zhengtao Wang, Ce Zhu, Zhiqiang Xia, Qi Guo, Yipeng Liu
Deep network pruning is an effective method to reduce the storage and computation cost of deep neural networks when applying them to resource-limited devices.
no code implementations • 9 Feb 2017 • Qi Guo, Ce Zhu, Zhiqiang Xia, Zhengtao Wang, Yipeng Liu
In this paper, we propose a deep generative model to synthesize face photo from simple line drawing controlled by face attributes such as hair color and complexion.
1 code implementation • 15 Aug 2016 • Zhiqiang Xia, Ce Zhu, Zhengtao Wang, Qi Guo, Yipeng Liu
We also demonstrate that style of images could be a combination of these texture primitives.
1 code implementation • 28 Mar 2016 • Jingbo Zhou, Qi Guo, H. V. Jagadish, Luboš Krčál, Siyuan Liu, Wenhao Luan, Anthony K. H. Tung, Yueji Yang, Yuxin Zheng
We propose a novel generic inverted index framework on the GPU (called GENIE), aiming to reduce the programming complexity of the GPU for parallel similarity search of different data types.
no code implementations • 28 Nov 2015 • Qi Guo, Le Dan, Dong Yin, Xiangyang Ji
Multi-object tracking remains challenging due to frequent occurrence of occlusions and outliers.
no code implementations • 29 Apr 2015 • Qi Guo, Zixuan Wang, Ming Li, Hamid Aghajan
The time people spend in front of computers has been increasing steadily due to the role computers play in modern society.
no code implementations • 29 Jan 2015 • Qi Guo, Bo-Wei Chen, Feng Jiang, Xiangyang Ji, Sun-Yuan Kung
Firstly, we divide the feature space into several subspaces using the decomposition method proposed in this paper.