Search Results for author: Qi Guo

Found 46 papers, 14 papers with code

Collaborative Large Language Model for Recommender Systems

1 code implementation2 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.

Language Modelling Large Language Model +1

Polarization Multi-Image Synthesis with Birefringent Metasurfaces

1 code implementation16 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.

Image Generation

Pushing the Limits of Machine Design: Automated CPU Design with AI

1 code implementation21 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.

Online Prototype Alignment for Few-shot Policy Transfer

1 code implementation12 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.

Domain Adaptation Reinforcement Learning (RL)

Path-Specific Counterfactual Fairness for Recommender Systems

1 code implementation5 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.

Blocking counterfactual +4

Flew Over Learning Trap: Learn Unlearnable Samples by Progressive Staged Training

1 code implementation3 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.

Unlearnable Examples for Diffusion Models: Protect Data from Unauthorized Exploitation

no code implementations2 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.

Denoising Image Generation

ANPL: Towards Natural Programming with Interactive Decomposition

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.

Code Generation Program Synthesis

Conceptual Reinforcement Learning for Language-Conditioned Tasks

no code implementations9 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.

reinforcement-learning Reinforcement Learning (RL)

Ultra-low Precision Multiplication-free Training for Deep Neural Networks

no code implementations28 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.


Online Symbolic Regression with Informative Query

no code implementations21 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.

regression Symbolic Regression

Quantized Distributed Training of Large Models with Convergence Guarantees

no code implementations5 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).


Dual Class-Aware Contrastive Federated Semi-Supervised Learning

no code implementations16 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.

StereoISP: Rethinking Image Signal Processing for Dual Camera Systems

no code implementations11 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.

Causality-driven Hierarchical Structure Discovery for Reinforcement Learning

no code implementations13 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

Object-Category Aware Reinforcement Learning

no code implementations13 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.

Feature Engineering Object Discovery +2

Multivariate Hawkes-based Models in LOB: European, Spread and Basket Option Pricing

no code implementations15 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.

Remote Work Optimization with Robust Multi-channel Graph Neural Networks

no code implementations26 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.

Vocal Bursts Type Prediction

FedMCSA: Personalized Federated Learning via Model Components Self-Attention

no code implementations23 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.

Personalized Federated Learning

Neural Program Synthesis with Query

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.

Program Synthesis

ScaleCert: Scalable Certified Defense against Adversarial Patches with Sparse Superficial Layers

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.

Hindsight Value Function for Variance Reduction in Stochastic Dynamic Environment

1 code implementation26 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.

Policy Gradient Methods

Improving Dialogue Breakdown Detection with Semi-Supervised Learning

no code implementations30 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.

Data Augmentation

MOTS: Multiple Object Tracking for General Categories Based On Few-Shot Method

no code implementations19 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.

Multi-Object Tracking Multiple Object Tracking

DWM: A Decomposable Winograd Method for Convolution Acceleration

no code implementations3 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.

Talent Search and Recommendation Systems at LinkedIn: Practical Challenges and Lessons Learned

no code implementations18 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.

Information Retrieval Recommendation Systems +1

Tackling 3D ToF Artifacts Through Learning and the FLAT Dataset

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.

BENCHIP: Benchmarking Intelligence Processors

no code implementations23 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).


Focal Track: Depth and Accommodation With Oscillating Lens Deformation

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.

Towards thinner convolutional neural networks through Gradually Global Pruning

no code implementations29 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.

Network Pruning

Attribute-controlled face photo synthesis from simple line drawing

no code implementations9 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.

Every Filter Extracts A Specific Texture In Convolutional Neural Networks

1 code implementation15 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.

A Generic Inverted Index Framework for Similarity Search on the GPU - Technical Report

1 code implementation28 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.

Sliding-Window Optimization on an Ambiguity-Clearness Graph for Multi-object Tracking

no code implementations28 Nov 2015 Qi Guo, Le Dan, Dong Yin, Xiangyang Ji

Multi-object tracking remains challenging due to frequent occurrence of occlusions and outliers.

Multi-Object Tracking

Intelligent Health Recommendation System for Computer Users

no code implementations29 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.

Efficient Divide-And-Conquer Classification Based on Feature-Space Decomposition

no code implementations29 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.

Classification General Classification

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