Search Results for author: Yan Zheng

Found 61 papers, 10 papers with code

Hessian-aware Quantized Node Embeddings for Recommendation

no code implementations2 Sep 2023 Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang

To address the gradient mismatch problem in STE, we further consider the quantized errors and its second-order derivatives for better stability.

Recommendation Systems Retrieval

Adversarial Collaborative Filtering for Free

no code implementations20 Aug 2023 Huiyuan Chen, Xiaoting Li, Vivian Lai, Chin-Chia Michael Yeh, Yujie Fan, Yan Zheng, Mahashweta Das, Hao Yang

In this paper, we present Sharpness-aware Collaborative Filtering (SharpCF), a simple yet effective method that conducts adversarial training without extra computational cost over the base optimizer.

Collaborative Filtering

EmbeddingTree: Hierarchical Exploration of Entity Features in Embedding

no code implementations2 Aug 2023 Yan Zheng, Junpeng Wang, Chin-Chia Michael Yeh, Yujie Fan, Huiyuan Chen, Liang Wang, Wei zhang

The tool helps users discover nuance features of data entities, perform feature denoising/injecting in embedding training, and generate embeddings for unseen entities.


BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization

1 code implementation1 Aug 2023 Junyi Wang, Yuanyang Zhu, Zhi Wang, Yan Zheng, Jianye Hao, Chunlin Chen

Evolutionary reinforcement learning (ERL) algorithms recently raise attention in tackling complex reinforcement learning (RL) problems due to high parallelism, while they are prone to insufficient exploration or model collapse without carefully tuning hyperparameters (aka meta-parameters).

Bilevel Optimization reinforcement-learning +1

Prioritized Trajectory Replay: A Replay Memory for Data-driven Reinforcement Learning

no code implementations27 Jun 2023 Jinyi Liu, Yi Ma, Jianye Hao, Yujing Hu, Yan Zheng, Tangjie Lv, Changjie Fan

In summary, our research emphasizes the significance of trajectory-based data sampling techniques in enhancing the efficiency and performance of offline RL algorithms.

D4RL Offline RL +2

Improving Offline-to-Online Reinforcement Learning with Q-Ensembles

no code implementations12 Jun 2023 Kai Zhao, Yi Ma, Jianye Hao, Jinyi Liu, Yan Zheng, Zhaopeng Meng

Offline reinforcement learning (RL) is a learning paradigm where an agent learns from a fixed dataset of experience.

Offline RL reinforcement-learning +1

HIPODE: Enhancing Offline Reinforcement Learning with High-Quality Synthetic Data from a Policy-Decoupled Approach

no code implementations10 Jun 2023 Shixi Lian, Yi Ma, Jinyi Liu, Yan Zheng, Zhaopeng Meng

Offline reinforcement learning (ORL) has gained attention as a means of training reinforcement learning models using pre-collected static data.

D4RL Data Augmentation +1

In-Sample Policy Iteration for Offline Reinforcement Learning

no code implementations9 Jun 2023 Xiaohan Hu, Yi Ma, Chenjun Xiao, Yan Zheng, Zhaopeng Meng

In this paper, we propose a novel algorithm employing in-sample policy iteration that substantially enhances behavior-regularized methods in offline RL.

D4RL Offline RL +2

Prompt Injection attack against LLM-integrated Applications

no code implementations8 Jun 2023 Yi Liu, Gelei Deng, Yuekang Li, Kailong Wang, Tianwei Zhang, Yepang Liu, Haoyu Wang, Yan Zheng, Yang Liu

We deploy HouYi on 36 actual LLM-integrated applications and discern 31 applications susceptible to prompt injection.

PDT: Pretrained Dual Transformers for Time-aware Bipartite Graphs

no code implementations2 Jun 2023 Xin Dai, Yujie Fan, Zhongfang Zhuang, Shubham Jain, Chin-Chia Michael Yeh, Junpeng Wang, Liang Wang, Yan Zheng, Wei zhang

Pre-training on large models is prevalent and emerging with the ever-growing user-generated content in many machine learning application categories.

Contrastive Learning

MetaDiffuser: Diffusion Model as Conditional Planner for Offline Meta-RL

no code implementations31 May 2023 Fei Ni, Jianye Hao, Yao Mu, Yifu Yuan, Yan Zheng, Bin Wang, Zhixuan Liang

Recently, diffusion model shines as a promising backbone for the sequence modeling paradigm in offline reinforcement learning(RL).

Reinforcement Learning (RL)

Generative Flow Networks for Precise Reward-Oriented Active Learning on Graphs

no code implementations24 Apr 2023 Yinchuan Li, Zhigang Li, Wenqian Li, Yunfeng Shao, Yan Zheng, Jianye Hao

Many score-based active learning methods have been successfully applied to graph-structured data, aiming to reduce the number of labels and achieve better performance of graph neural networks based on predefined score functions.

Active Learning

How Does Attention Work in Vision Transformers? A Visual Analytics Attempt

no code implementations24 Mar 2023 Yiran Li, Junpeng Wang, Xin Dai, Liang Wang, Chin-Chia Michael Yeh, Yan Zheng, Wei zhang, Kwan-Liu Ma

Multi-head self-attentions are then applied to the sequence to learn the attention between patches.

Neural Episodic Control with State Abstraction

no code implementations27 Jan 2023 Zhuo Li, Derui Zhu, Yujing Hu, Xiaofei Xie, Lei Ma, Yan Zheng, Yan Song, Yingfeng Chen, Jianjun Zhao

Generally, episodic control-based approaches are solutions that leverage highly-rewarded past experiences to improve sample efficiency of DRL algorithms.

OpenAI Gym

Denoising Self-attentive Sequential Recommendation

no code implementations8 Dec 2022 Huiyuan Chen, Yusan Lin, Menghai Pan, Lan Wang, Chin-Chia Michael Yeh, Xiaoting Li, Yan Zheng, Fei Wang, Hao Yang

Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies.

Denoising Sequential Recommendation

TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems

no code implementations8 Dec 2022 Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang

We found that our TinyKG with INT2 quantization aggressively reduces the memory footprint of activation maps with $7 \times$, only with $2\%$ loss in accuracy, allowing us to deploy KGNNs on memory-constrained devices.

Knowledge Graphs Quantization +1

Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces

no code implementations AMTA 2022 Prince O Aboagye, Yan Zheng, Michael Yeh, Junpeng Wang, Zhongfang Zhuang, Huiyuan Chen, Liang Wang, Wei zhang, Jeff Phillips

Optimal Transport (OT) provides a useful geometric framework to estimate the permutation matrix under unsupervised cross-lingual word embedding (CLWE) models that pose the alignment task as a Wasserstein-Procrustes problem.

Bilingual Lexicon Induction Quantization

ERL-Re$^2$: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation

1 code implementation26 Oct 2022 Jianye Hao, Pengyi Li, Hongyao Tang, Yan Zheng, Xian Fu, Zhaopeng Meng

The state representation conveys expressive common features of the environment learned by all the agents collectively; the linear policy representation provides a favorable space for efficient policy optimization, where novel behavior-level crossover and mutation operations can be performed.

Continuous Control Evolutionary Algorithms +2

Neural Volumetric Mesh Generator

no code implementations6 Oct 2022 Yan Zheng, Lemeng Wu, Xingchao Liu, Zhen Chen, Qiang Liu, QiXing Huang

We first propose a diffusion-based generative model to tackle this problem by generating voxelized shapes with close-to-reality outlines and structures.

EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model

no code implementations2 Oct 2022 Yifu Yuan, Jianye Hao, Fei Ni, Yao Mu, Yan Zheng, Yujing Hu, Jinyi Liu, Yingfeng Chen, Changjie Fan

Unsupervised reinforcement learning (URL) poses a promising paradigm to learn useful behaviors in a task-agnostic environment without the guidance of extrinsic rewards to facilitate the fast adaptation of various downstream tasks.

reinforcement-learning Reinforcement Learning (RL) +2

Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes

no code implementations16 Sep 2022 Min Zhang, Hongyao Tang, Jianye Hao, Yan Zheng

First, we propose a unified policy abstraction theory, containing three types of policy abstraction associated to policy features at different levels.

Decision Making Metric Learning +2

Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph

no code implementations11 Aug 2022 Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng, Huiyuan Chen, Javid Ebrahimi, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei zhang

Graph neural networks (GNNs) are deep learning models designed specifically for graph data, and they typically rely on node features as the input to the first layer.

Representation Learning

HIFI-Net: A Novel Network for Enhancement to Underwater Images

no code implementations6 Jun 2022 Jiajia Zhou, Junbin Zhuang, Yan Zheng, Di wu

As this network make "Haar Images into Fusion Images", it is called HIFI-Net.

GALOIS: Boosting Deep Reinforcement Learning via Generalizable Logic Synthesis

no code implementations27 May 2022 Yushi Cao, Zhiming Li, Tianpei Yang, Hao Zhang, Yan Zheng, Yi Li, Jianye Hao, Yang Liu

In this paper, we combine the above two paradigms together and propose a novel Generalizable Logic Synthesis (GALOIS) framework to synthesize hierarchical and strict cause-effect logic programs.

Decision Making Program Synthesis +2

Relational Representation Learning in Visually-Rich Documents

no code implementations5 May 2022 Xin Li, Yan Zheng, Yiqing Hu, Haoyu Cao, Yunfei Wu, Deqiang Jiang, Yinsong Liu, Bo Ren

To deal with the unpredictable definition of relations, we propose a novel contrastive learning task named Relational Consistency Modeling (RCM), which harnesses the fact that existing relations should be consistent in differently augmented positive views.

Contrastive Learning Key Information Extraction +1

PAnDR: Fast Adaptation to New Environments from Offline Experiences via Decoupling Policy and Environment Representations

no code implementations6 Apr 2022 Tong Sang, Hongyao Tang, Yi Ma, Jianye Hao, Yan Zheng, Zhaopeng Meng, Boyan Li, Zhen Wang

In online adaptation phase, with the environment context inferred from few experiences collected in new environments, the policy is optimized by gradient ascent with respect to the PDVF.

Contrastive Learning Decision Making

Revealing Reliable Signatures by Learning Top-Rank Pairs

no code implementations17 Mar 2022 Xiaotong Ji, Yan Zheng, Daiki Suehiro, Seiichi Uchida

Signature verification, as a crucial practical documentation analysis task, has been continuously studied by researchers in machine learning and pattern recognition fields.


PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Information Collaboration

1 code implementation16 Mar 2022 Pengyi Li, Hongyao Tang, Tianpei Yang, Xiaotian Hao, Tong Sang, Yan Zheng, Jianye Hao, Matthew E. Taylor, Wenyuan Tao, Zhen Wang, Fazl Barez

However, we reveal sub-optimal collaborative behaviors also emerge with strong correlations, and simply maximizing the MI can, surprisingly, hinder the learning towards better collaboration.

Multi-agent Reinforcement Learning reinforcement-learning +1

Breaking the Curse of Dimensionality in Multiagent State Space: A Unified Agent Permutation Framework

no code implementations10 Mar 2022 Xiaotian Hao, Hangyu Mao, Weixun Wang, Yaodong Yang, Dong Li, Yan Zheng, Zhen Wang, Jianye Hao

To break this curse, we propose a unified agent permutation framework that exploits the permutation invariance (PI) and permutation equivariance (PE) inductive biases to reduce the multiagent state space.

Data Augmentation Reinforcement Learning (RL) +1

Learning-From-Disagreement: A Model Comparison and Visual Analytics Framework

no code implementations19 Jan 2022 Junpeng Wang, Liang Wang, Yan Zheng, Chin-Chia Michael Yeh, Shubham Jain, Wei zhang

With these metrics, one can easily identify meta-features with the most complementary behaviors in two classifiers, and use them to better ensemble the classifiers.

Binary Classification

ED2: An Environment Dynamics Decomposition Framework for World Model Construction

1 code implementation6 Dec 2021 Cong Wang, Tianpei Yang, Jianye Hao, Yan Zheng, Hongyao Tang, Fazl Barez, Jinyi Liu, Jiajie Peng, Haiyin Piao, Zhixiao Sun

To reduce the model error, previous works use a single well-designed network to fit the entire environment dynamics, which treats the environment dynamics as a black box.

Model-based Reinforcement Learning

Uncertainty-aware Low-Rank Q-Matrix Estimation for Deep Reinforcement Learning

no code implementations19 Nov 2021 Tong Sang, Hongyao Tang, Jianye Hao, Yan Zheng, Zhaopeng Meng

Such a reconstruction exploits the underlying structure of value matrix to improve the value approximation, thus leading to a more efficient learning process of value function.

Continuous Control reinforcement-learning +1

Embedding Compression with Hashing for Efficient Representation Learning in Graph

no code implementations29 Sep 2021 Chin-Chia Michael Yeh, Mengting Gu, Yan Zheng, Huiyuan Chen, Javid Ebrahimi, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei zhang

When applying such type of networks on graph without node feature, one can extract simple graph-based node features (e. g., number of degrees) or learn the input node representation (i. e., embeddings) when training the network.

Representation Learning

Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks

no code implementations21 Sep 2021 Chin-Chia Michael Yeh, Zhongfang Zhuang, Junpeng Wang, Yan Zheng, Javid Ebrahimi, Ryan Mercer, Liang Wang, Wei zhang

In this work, we study the problem of multivariate time series prediction for estimating transaction metrics associated with entities in the payment transaction database.

Time Series Time Series Prediction

Towards Book Cover Design via Layout Graphs

1 code implementation24 May 2021 Wensheng Zhang, Yan Zheng, Taiga Miyazono, Seiichi Uchida, Brian Kenji Iwana

Book covers are intentionally designed and provide an introduction to a book.

Normalization of Language Embeddings for Cross-Lingual Alignment

1 code implementation NeurIPS 2021 Prince Osei Aboagye, Jeff Phillips, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei zhang, Liang Wang, Hao Yang

Learning a good transfer function to map the word vectors from two languages into a shared cross-lingual word vector space plays a crucial role in cross-lingual NLP.


VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations

1 code implementation6 Apr 2021 Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei zhang, Bei Wang

To aid this, we present Visualization of Embedding Representations for deBiasing system ("VERB"), an open-source web-based visualization tool that helps the users gain a technical understanding and visual intuition of the inner workings of debiasing techniques, with a focus on their geometric properties.

Decision Making Dimensionality Reduction +3

MQES: Max-Q Entropy Search for Efficient Exploration in Continuous Reinforcement Learning

no code implementations1 Jan 2021 Jinyi Liu, Zhi Wang, Jianye Hao, Yan Zheng

Recently, the principle of optimism in the face of (aleatoric and epistemic) uncertainty has been utilized to design efficient exploration strategies for Reinforcement Learning (RL).

Efficient Exploration reinforcement-learning +1

Merchant Category Identification Using Credit Card Transactions

no code implementations5 Nov 2020 Chin-Chia Michael Yeh, Zhongfang Zhuang, Yan Zheng, Liang Wang, Junpeng Wang, Wei zhang

In this work, we approach this problem from a multi-modal learning perspective, where we use not only the merchant time series data but also the information of merchant-merchant relationship (i. e., affinity) to verify the self-reported business type (i. e., merchant category) of a given merchant.

Time Series Time Series Analysis +1

Towards a Flexible Embedding Learning Framework

no code implementations23 Sep 2020 Chin-Chia Michael Yeh, Dhruv Gelda, Zhongfang Zhuang, Yan Zheng, Liang Gou, Wei zhang

Our proposed framework utilizes a set of entity-relation-matrices as the input, which quantifies the affinities among different entities in the database.

Representation Learning

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

no code implementations14 May 2020 Jianwen Sun, Tianwei Zhang, Xiaofei Xie, Lei Ma, Yan Zheng, Kangjie Chen, Yang Liu

Adversarial attacks against conventional Deep Learning (DL) systems and algorithms have been widely studied, and various defenses were proposed.

Adversarial Attack reinforcement-learning +1

Continuous Multiagent Control using Collective Behavior Entropy for Large-Scale Home Energy Management

no code implementations14 May 2020 Jianwen Sun, Yan Zheng, Jianye Hao, Zhaopeng Meng, Yang Liu

With the increasing popularity of electric vehicles, distributed energy generation and storage facilities in smart grid systems, an efficient Demand-Side Management (DSM) is urgent for energy savings and peak loads reduction.

energy management Management

KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge

no code implementations18 Feb 2020 Peng Zhang, Jianye Hao, Weixun Wang, Hongyao Tang, Yi Ma, Yihai Duan, Yan Zheng

Our framework consists of a fuzzy rule controller to represent human knowledge and a refine module to fine-tune suboptimal prior knowledge.

Common Sense Reasoning Continuous Control +2

Constrained Non-Affine Alignment of Embeddings

no code implementations13 Oct 2019 Yuwei Wang, Yan Zheng, Yanqing Peng, Chin-Chia Michael Yeh, Zhongfang Zhuang, Das Mahashweta, Bendre Mangesh, Feifei Li, Wei zhang, Jeff M. Phillips

Embeddings are already essential tools for large language models and image analysis, and their use is being extended to many other research domains.

Gradient Boosting Survival Tree with Applications in Credit Scoring

1 code implementation9 Aug 2019 Miaojun Bai, Yan Zheng, Yun Shen

In order to deal with highly heterogeneous industrial data collected in Chinese market of consumer finance, we propose a nonparametric ensemble tree model called gradient boosting survival tree (GBST) that extends the survival tree models with a gradient boosting algorithm.

Survival Analysis

A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents

no code implementations NeurIPS 2018 Yan Zheng, Zhaopeng Meng, Jianye Hao, Zongzhang Zhang, Tianpei Yang, Changjie Fan

In multiagent domains, coping with non-stationary agents that change behaviors from time to time is a challenging problem, where an agent is usually required to be able to quickly detect the other agent's policy during online interaction, and then adapt its own policy accordingly.

Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints from Limited Training Data

1 code implementation ICCV 2019 Yutong Bai, Qing Liu, Lingxi Xie, Weichao Qiu, Yan Zheng, Alan Yuille

In particular, this enables images in the training dataset to be matched to a virtual 3D model of the object (for simplicity, we assume that the object viewpoint can be estimated by standard techniques).

Clustering Semantic Part Detection

Hierarchical Deep Multiagent Reinforcement Learning with Temporal Abstraction

no code implementations25 Sep 2018 Hongyao Tang, Jianye Hao, Tangjie Lv, Yingfeng Chen, Zongzhang Zhang, Hangtian Jia, Chunxu Ren, Yan Zheng, Zhaopeng Meng, Changjie Fan, Li Wang

Besides, we propose a new experience replay mechanism to alleviate the issue of the sparse transitions at the high level of abstraction and the non-stationarity of multiagent learning.

reinforcement-learning Reinforcement Learning (RL)

Towards Efficient Detection and Optimal Response against Sophisticated Opponents

no code implementations12 Sep 2018 Tianpei Yang, Zhaopeng Meng, Jianye Hao, Chongjie Zhang, Yan Zheng, Ze Zheng

This paper proposes a novel approach called Bayes-ToMoP which can efficiently detect the strategy of opponents using either stationary or higher-level reasoning strategies.

Multiagent Systems

End-to-End Neural Ranking for eCommerce Product Search: an application of task models and textual embeddings

no code implementations19 Jun 2018 Brenner Eliot, Zhao Jun, Kutiyanawala Aliasgar, Yan Zheng

The different types of relevance models developed for IR have complementary advantages and disadvantages when applied to eCommerce product search.


Interactive Deep Colorization With Simultaneous Global and Local Inputs

no code implementations27 Jan 2018 Yi Xiao, Peiyao Zhou, Yan Zheng

To solve this problem, we present a novel deep colorization method, which allows simultaneous global and local inputs to better control the output colorized images.


Joint convolutional neural pyramid for depth map super-resolution

no code implementations3 Jan 2018 Yi Xiao, Xiang Cao, Xianyi Zhu, Renzhi Yang, Yan Zheng

The convolutional neural pyramids extract information from large receptive fields of the depth map and guidance map, while the convolutional neural network effectively transfers useful structures of the guidance image to the depth image.

Depth Map Super-Resolution

Coresets for Kernel Regression

no code implementations13 Feb 2017 Yan Zheng, Jeff M. Phillips

Kernel regression is an essential and ubiquitous tool for non-parametric data analysis, particularly popular among time series and spatial data.

regression Time Series +1

Subsampling in Smoothed Range Spaces

no code implementations30 Oct 2015 Jeff M. Phillips, Yan Zheng

We consider smoothed versions of geometric range spaces, so an element of the ground set (e. g. a point) can be contained in a range with a non-binary value in $[0, 1]$.

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