Search Results for author: Yang Yu

Found 112 papers, 29 papers with code

Exploring Intra- and Inter-Video Relation for Surgical Semantic Scene Segmentation

no code implementations29 Mar 2022 Yueming Jin, Yang Yu, Cheng Chen, Zixu Zhao, Pheng-Ann Heng, Danail Stoyanov

Automatic surgical scene segmentation is fundamental for facilitating cognitive intelligence in the modern operating theatre.

Contrastive Learning Scene Segmentation

Enhancing Neural Mathematical Reasoning by Abductive Combination with Symbolic Library

no code implementations28 Mar 2022 Yangyang Hu, Yang Yu

On a mathematical reasoning dataset, we adopt the recently proposed abductive learning framework, and propose the ABL-Sym algorithm that combines the Transformer neural models with a symbolic mathematics library.

Mathematical Reasoning Translation

A Note on Target Q-learning For Solving Finite MDPs with A Generative Oracle

no code implementations22 Mar 2022 Ziniu Li, Tian Xu, Yang Yu

In particular, we demonstrate that the sample complexity of the target Q-learning algorithm in [Lee and He, 2020] is $\widetilde{\mathcal O}(|\mathcal S|^2|\mathcal A|^2 (1-\gamma)^{-5}\varepsilon^{-2})$.


Multi-Agent Policy Transfer via Task Relationship Modeling

no code implementations9 Mar 2022 Rongjun Qin, Feng Chen, Tonghan Wang, Lei Yuan, Xiaoran Wu, Zongzhang Zhang, Chongjie Zhang, Yang Yu

We demonstrate that the task representation can capture the relationship among tasks, and can generalize to unseen tasks.

Transfer Learning

UA-FedRec: Untargeted Attack on Federated News Recommendation

1 code implementation14 Feb 2022 Jingwei Yi, Fangzhao Wu, Bin Zhu, Yang Yu, Chao Zhang, Guangzhong Sun, Xing Xie

Our study reveals a critical security issue in existing federated news recommendation systems and calls for research efforts to address the issue.

Federated Learning News Recommendation +1

Rethinking ValueDice: Does It Really Improve Performance?

no code implementations5 Feb 2022 Ziniu Li, Tian Xu, Yang Yu, Zhi-Quan Luo

First, we show that ValueDice could reduce to BC under the offline setting.

Imitation Learning

Online Allocation with Two-sided Resource Constraints

no code implementations28 Dec 2021 Qixin Zhang, Wenbing Ye, Zaiyi Chen, Haoyuan Hu, Enhong Chen, Yang Yu

Moreover, an optimization method to estimate the optimal measure of feasibility is proposed with theoretical guarantee at the end of this paper.

Progressive Multi-stage Interactive Training in Mobile Network for Fine-grained Recognition

no code implementations8 Dec 2021 Zhenxin Wu, Qingliang Chen, Yifeng Liu, Yinqi Zhang, Chengkai Zhu, Yang Yu

Finally, using the progressive training (P), the features extracted by the model in different stages can be fully utilized and fused with each other.

Fine-Grained Image Classification

Tiny-NewsRec: Efficient and Effective PLM-based News Recommendation

no code implementations2 Dec 2021 Yang Yu, Fangzhao Wu, Chuhan Wu, Jingwei Yi, Tao Qi, Qi Liu

Recently, pre-trained language models (PLMs) have demonstrated the great capability of natural language understanding and the potential of improving news modeling for news recommendation.

Knowledge Distillation Natural Language Understanding +1

Offline Model-based Adaptable Policy Learning

1 code implementation NeurIPS 2021 Xiong-Hui Chen, Yang Yu, Qingyang Li, Fan-Ming Luo, Zhiwei Qin, Wenjie Shang, Jieping Ye

Current offline reinforcement learning methods commonly learn in the policy space constrained to in-support regions by the offline dataset, in order to ensure the robustness of the outcome policies.

Decision Making reinforcement-learning

Cross-modal Domain Adaptation for Cost-Efficient Visual Reinforcement Learning

1 code implementation NeurIPS 2021 Xiong-Hui Chen, Shengyi Jiang, Feng Xu, Zongzhang Zhang, Yang Yu

Experiments on MuJoCo and Hand Manipulation Suite tasks show that the agents deployed with our method achieve similar performance as it has in the source domain, while those deployed with previous methods designed for same-modal domain adaptation suffer a larger performance gap.

Domain Adaptation reinforcement-learning

Stochastic optimal scheduling of demand response-enabled microgrids with renewable generations: An analytical-heuristic approach

no code implementations24 Nov 2021 Yang Li, Kang Li, Zhen Yang, Yang Yu, Runnan Xu, Miaosen Yang

In order to solve this model, this research combines Jaya algorithm and interior point method (IPM) to develop a hybrid analysis-heuristic solution method called Jaya-IPM, where the lower- and upper- levels are respectively addressed by the IPM and the Jaya, and the scheduling scheme is obtained via iterations between the two levels.

Calculus of Consent via MARL: Legitimating the Collaborative Governance Supplying Public Goods

no code implementations20 Nov 2021 Yang Hu, Zhui Zhu, Sirui Song, Xue Liu, Yang Yu

Experimental results in an exemplary environment show that our MARL approach is able to demonstrate the effectiveness and necessity of restrictions on individual liberty for collaborative supply of public goods.

Multi-agent Reinforcement Learning

Learning Efficient Online 3D Bin Packing on Packing Configuration Trees

1 code implementation ICLR 2022 Hang Zhao, Yang Yu, Kai Xu

PCT is a full-fledged description of the state and action space of bin packing which can support packing policy learning based on deep reinforcement learning (DRL).

3D Bin Packing

UserBERT: Contrastive User Model Pre-training

no code implementations3 Sep 2021 Chuhan Wu, Fangzhao Wu, Yang Yu, Tao Qi, Yongfeng Huang, Xing Xie

Two self-supervision tasks are incorporated in UserBERT for user model pre-training on unlabeled user behavior data to empower user modeling.

Neural-to-Tree Policy Distillation with Policy Improvement Criterion

no code implementations16 Aug 2021 Zhao-Hua Li, Yang Yu, Yingfeng Chen, Ke Chen, Zhipeng Hu, Changjie Fan

The empirical results show that the proposed method can preserve a higher cumulative reward than behavior cloning and learn a more consistent policy to the original one.

Decision Making reinforcement-learning

PatrickStar: Parallel Training of Pre-trained Models via Chunk-based Memory Management

1 code implementation12 Aug 2021 Jiarui Fang, Yang Yu, Zilin Zhu, Shenggui Li, Yang You, Jie zhou

Therefore, we proposed a system called PatrickStar to lower the hardware requirements of PTMs and make them accessible to everyone.

On Generalization of Adversarial Imitation Learning and Beyond

no code implementations19 Jun 2021 Tian Xu, Ziniu Li, Yang Yu, Zhi-Quan Luo

For some MDPs, we show that vanilla AIL has a worse sample complexity than BC.

Imitation Learning

HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation

no code implementations ACL 2021 Tao Qi, Fangzhao Wu, Chuhan Wu, Peiru Yang, Yang Yu, Xing Xie, Yongfeng Huang

Instead of a single user embedding, in our method each user is represented in a hierarchical interest tree to better capture their diverse and multi-grained interest in news.

News Recommendation

Context-Aware Sparse Deep Coordination Graphs

no code implementations ICLR 2022 Tonghan Wang, Liang Zeng, Weijun Dong, Qianlan Yang, Yang Yu, Chongjie Zhang

We carry out a case study and experiments on the MACO and StarCraft II micromanagement benchmark to demonstrate the dynamics of sparse graph learning, the influence of graph sparseness, and the learning performance of our method.

graph construction Graph Learning +2

Active Hierarchical Exploration with Stable Subgoal Representation Learning

1 code implementation ICLR 2022 Siyuan Li, Jin Zhang, Jianhao Wang, Yang Yu, Chongjie Zhang

Although GCHRL possesses superior exploration ability by decomposing tasks via subgoals, existing GCHRL methods struggle in temporally extended tasks with sparse external rewards, since the high-level policy learning relies on external rewards.

Continuous Control Hierarchical Reinforcement Learning +1

Sparsity Prior Regularized Q-learning for Sparse Action Tasks

no code implementations18 May 2021 Jing-Cheng Pang, Tian Xu, Sheng-Yi Jiang, Yu-Ren Liu, Yang Yu

In many decision-making tasks, some specific actions are limited in their frequency or total amounts, such as "fire" in the gunfight game and "buy/sell" in the stock trading.

Decision Making Q-Learning

An Introduction of mini-AlphaStar

1 code implementation14 Apr 2021 Ruo-Ze Liu, Wenhai Wang, Yanjie Shen, Zhiqi Li, Yang Yu, Tong Lu

StarCraft II (SC2) is a real-time strategy game in which players produce and control multiple units to fight against opponent's units.

reinforcement-learning Starcraft +1

Distributed Bootstrap for Simultaneous Inference Under High Dimensionality

1 code implementation19 Feb 2021 Yang Yu, Shih-Kang Chao, Guang Cheng

We propose a distributed bootstrap method for simultaneous inference on high-dimensional massive data that are stored and processed with many machines.

Derivative-Free Reinforcement Learning: A Review

no code implementations10 Feb 2021 Hong Qian, Yang Yu

In this article, we summarize methods of derivative-free reinforcement learning to date, and organize the methods in aspects including parameter updating, model selection, exploration, and parallel/distributed methods.

Model Selection reinforcement-learning

NewsBERT: Distilling Pre-trained Language Model for Intelligent News Application

no code implementations Findings (EMNLP) 2021 Chuhan Wu, Fangzhao Wu, Yang Yu, Tao Qi, Yongfeng Huang, Qi Liu

However, existing language models are pre-trained and distilled on general corpus like Wikipedia, which has some gaps with the news domain and may be suboptimal for news intelligence.

Knowledge Distillation Language Modelling +1

The Flare and Warp of the Young Stellar Disk traced with LAMOST DR5 OB-type stars

no code implementations1 Feb 2021 Yang Yu, Hai-Feng Wang, Wen-Yuan Cui, Lin-Lin Li, Chao Liu, Bo Zhang, Hao Tian, Zhen-Yan Huo, Jie Ju, Zhi-Cun Liu, Fang Wen, Shuai Feng

We present analysis of the spatial density structure for the outer disk from 8$-$14 \, kpc with the LAMOST DR5 13534 OB-type stars and observe similar flaring on north and south sides of the disk implying that the flaring structure is symmetrical about the Galactic plane, for which the scale height at different Galactocentric distance is from 0. 14 to 0. 5 \, kpc.

Astrophysics of Galaxies

NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning

3 code implementations1 Feb 2021 Rongjun Qin, Songyi Gao, Xingyuan Zhang, Zhen Xu, Shengkai Huang, Zewen Li, Weinan Zhang, Yang Yu

We evaluate existing offline RL algorithms on NeoRL and argue that the performance of a policy should also be compared with the deterministic version of the behavior policy, instead of the dataset reward.

Offline RL reinforcement-learning

ASBSO: An Improved Brain Storm Optimization With Flexible Search Length and Memory-Based Selection

no code implementations27 Jan 2021 Yang Yu, Shangce Gao, Yirui Wang, Jiujun Cheng, Yuki Todo

This proposed method, adaptive step length based on memory selection BSO, namely ASBSO, applies multiple step lengths to modify the generation process of new solutions, thus supplying a flexible search according to corresponding problems and convergent periods.

Offline Adaptive Policy Leaning in Real-World Sequential Recommendation Systems

no code implementations1 Jan 2021 Xiong-Hui Chen, Yang Yu, Qingyang Li, Zhiwei Tony Qin, Wenjie Shang, Yiping Meng, Jieping Ye

Instead of increasing the fidelity of models for policy learning, we handle the distortion issue via learning to adapt to diverse simulators generated by the offline dataset.

Sequential Recommendation

Cross-Modal Domain Adaptation for Reinforcement Learning

1 code implementation1 Jan 2021 Xiong-Hui Chen, Shengyi Jiang, Feng Xu, Yang Yu

Domain adaptation is a promising direction for deploying RL agents in real-world applications, where vision-based robotics tasks constitute an important part.

Domain Adaptation reinforcement-learning

Interactive Search Based on Deep Reinforcement Learning

no code implementations9 Dec 2020 Yang Yu, Zhenhao Gu, Rong Tao, Jingtian Ge, Kenglun Chang

With the continuous development of machine learning technology, major e-commerce platforms have launched recommendation systems based on it to serve a large number of customers with different needs more efficiently.

Decision Making Recommendation Systems +1

Offline Imitation Learning with a Misspecified Simulator

no code implementations NeurIPS 2020 Shengyi Jiang, JingCheng Pang, Yang Yu

In this work, we investigate policy learning in the condition of a few expert demonstrations and a simulator with misspecified dynamics.

Decision Making Imitation Learning

OrgMining 2.0: A Novel Framework for Organizational Model Mining from Event Logs

no code implementations24 Nov 2020 Jing Yang, Chun Ouyang, Wil M. P. van der Aalst, Arthur H. M. ter Hofstede, Yang Yu

We demonstrate the feasibility of this framework by proposing an approach underpinned by the framework for organizational model discovery, and also conduct experiments on real-life event logs to discover and evaluate organizational models.

Model Discovery

Angular Embedding: A New Angular Robust Principal Component Analysis

no code implementations22 Nov 2020 Shenglan Liu, Yang Yu

As a widely used method in machine learning, principal component analysis (PCA) shows excellent properties for dimensionality reduction.

Dimensionality Reduction

RetroXpert: Decompose Retrosynthesis Prediction like a Chemist

1 code implementation NeurIPS 2020 Chaochao Yan, Qianggang Ding, Peilin Zhao, Shuangjia Zheng, Jinyu Yang, Yang Yu, Junzhou Huang

Retrosynthesis is the process of recursively decomposing target molecules into available building blocks.

Mining Generalized Features for Detecting AI-Manipulated Fake Faces

no code implementations27 Oct 2020 Yang Yu, Rongrong Ni, Yao Zhao

Recently, AI-manipulated face techniques have developed rapidly and constantly, which has raised new security issues in society.

Error Bounds of Imitating Policies and Environments

no code implementations NeurIPS 2020 Tian Xu, Ziniu Li, Yang Yu

In this paper, we firstly analyze the value gap between the expert policy and imitated policies by two imitation methods, behavioral cloning and generative adversarial imitation.

Imitation Learning Model-based Reinforcement Learning +1

Difference-in-Differences: Bridging Normalization and Disentanglement in PG-GAN

no code implementations16 Oct 2020 Xiao Liu, Jiajie Zhang, Siting Li, Zuotong Wu, Yang Yu

We discover that pixel normalization causes object entanglement by in-painting the area occupied by ablated objects.


TurboTransformers: An Efficient GPU Serving System For Transformer Models

no code implementations9 Oct 2020 Jiarui Fang, Yang Yu, Chengduo Zhao, Jie zhou

This paper designed a transformer serving system called TurboTransformers, which consists of a computing runtime and a serving framework to solve the above challenges.

Reinforced Epidemic Control: Saving Both Lives and Economy

1 code implementation4 Aug 2020 Sirui Song, Zefang Zong, Yong Li, Xue Liu, Yang Yu

Saving lives or economy is a dilemma for epidemic control in most cities while smart-tracing technology raises people's privacy concerns.


QPLEX: Duplex Dueling Multi-Agent Q-Learning

3 code implementations ICLR 2021 Jianhao Wang, Zhizhou Ren, Terry Liu, Yang Yu, Chongjie Zhang

This paper presents a novel MARL approach, called duPLEX dueling multi-agent Q-learning (QPLEX), which takes a duplex dueling network architecture to factorize the joint value function.

Decision Making Multi-agent Reinforcement Learning +3

Local Neighbor Propagation Embedding

no code implementations29 Jun 2020 Shenglan Liu, Yang Yu

Manifold Learning occupies a vital role in the field of nonlinear dimensionality reduction and its ideas also serve for other relevant methods.

Dimensionality Reduction

Affect inTweets: A Transfer Learning Approach

no code implementations LREC 2020 Linrui Zhang, Hsin-Lun Huang, Yang Yu, Dan Moldovan

As opposed to the traditional machine learning models which require considerable effort in designing task specific features, our model can be well adapted to the proposed tasks with a very limited amount of fine-tuning, which significantly reduces the manual effort in feature engineering.

Feature Engineering Transfer Learning

AliExpress Learning-To-Rank: Maximizing Online Model Performance without Going Online

no code implementations25 Mar 2020 Guangda Huzhang, Zhen-Jia Pang, Yongqing Gao, Yawen Liu, Weijie Shen, Wen-Ji Zhou, Qing Da, An-Xiang Zeng, Han Yu, Yang Yu, Zhi-Hua Zhou

The framework consists of an evaluator that generalizes to evaluate recommendations involving the context, and a generator that maximizes the evaluator score by reinforcement learning, and a discriminator that ensures the generalization of the evaluator.


Novelty-Prepared Few-Shot Classification

1 code implementation1 Mar 2020 Chao Wang, Ruo-Ze Liu, Han-Jia Ye, Yang Yu

We disclose that a classically fully trained feature extractor can leave little embedding space for unseen classes, which keeps the model from well-fitting the new classes.

Classification General Classification

Residual Bootstrap Exploration for Bandit Algorithms

no code implementations19 Feb 2020 Chi-Hua Wang, Yang Yu, Botao Hao, Guang Cheng

In this paper, we propose a novel perturbation-based exploration method in bandit algorithms with bounded or unbounded rewards, called residual bootstrap exploration (\texttt{ReBoot}).

Multi-Armed Bandits

Simultaneous Inference for Massive Data: Distributed Bootstrap

no code implementations ICML 2020 Yang Yu, Shih-Kang Chao, Guang Cheng

In this paper, we propose a bootstrap method applied to massive data processed distributedly in a large number of machines.

Temporal-adaptive Hierarchical Reinforcement Learning

no code implementations6 Feb 2020 Wen-Ji Zhou, Yang Yu

Hierarchical reinforcement learning (HRL) helps address large-scale and sparse reward issues in reinforcement learning.

Atari Games Hierarchical Reinforcement Learning +1

Robust Data-driven Profile-based Pricing Schemes

no code implementations12 Dec 2019 Jingshi Cui, Haoxiang Wang, Chenye Wu, Yang Yu

To enable an efficient electricity market, a good pricing scheme is of vital importance.

A Data-driven Storage Control Framework for Dynamic Pricing

no code implementations1 Dec 2019 Jiaman Wu, Zhiqi Wang, Chenye Wu, Kui Wang, Yang Yu

Dynamic pricing is both an opportunity and a challenge to the demand side.

Bridging Machine Learning and Logical Reasoning by Abductive Learning

1 code implementation NeurIPS 2019 Wang-Zhou Dai, Qiu-Ling Xu, Yang Yu, Zhi-Hua Zhou

In the area of artificial intelligence (AI), the two abilities are usually realised by machine learning and logic programming, respectively.

Improving Fictitious Play Reinforcement Learning with Expanding Models

no code implementations27 Nov 2019 Rong-Jun Qin, Jing-Cheng Pang, Yang Yu

However, learning to beat a pool in stochastic games, i. e., a wide distribution over policy models, is either sample-consuming or insufficient to exploit all models with limited amount of samples.


Vulnerability Analysis for Data Driven Pricing Schemes

no code implementations18 Nov 2019 Jingshi Cui, Haoxiang Wang, Chenye Wu, Yang Yu

In this paper, from an adversarial machine learning point of view, we examine the vulnerability of data-driven electricity market design.

Optimal Storage Control for Dynamic Pricing

no code implementations16 Nov 2019 Jiaman Wu, Zhiqi Wang, Yang Yu, Chenye Wu

Renewable energy brings huge uncertainties to the power system, which challenges the traditional power system operation with limited flexible resources.

Systems and Control Systems and Control Optimization and Control

On Value Discrepancy of Imitation Learning

no code implementations16 Nov 2019 Tian Xu, Ziniu Li, Yang Yu

We also show that the framework leads to the value discrepancy of GAIL in an order of O((1-\gamma)^{-1}).

Imitation Learning

Conductor Galloping Prediction on Imbalanced Datasets: SVM with Smart Sampling

no code implementations9 Nov 2019 Kui Wang, Jian Sun, Chenye Wu, Yang Yu

Conductor galloping is the high-amplitude, low-frequency oscillation of overhead power lines due to wind.

Signal Combination for Language Identification

no code implementations21 Oct 2019 Shengye Wang, Li Wan, Yang Yu, Ignacio Lopez Moreno

We compare the performance of a lattice-based ensemble model and a deep neural network model to combine signals from recognizers with that of a baseline that only uses low-level acoustic signals.

Language Identification Speech Recognition

Deep exploration by novelty-pursuit with maximum state entropy

no code implementations25 Sep 2019 Zi-Niu Li, Xiong-Hui Chen, Yang Yu

Efficient exploration is essential to reinforcement learning in huge state space.

Efficient Exploration

Hierarchic Neighbors Embedding

no code implementations16 Sep 2019 Shenglan Liu, Yang Yu, Yang Liu, Hong Qiao, Lin Feng, Jiashi Feng

Manifold learning now plays a very important role in machine learning and many relevant applications.

On the Robustness of Median Sampling in Noisy Evolutionary Optimization

no code implementations28 Jul 2019 Chao Bian, Chao Qian, Yang Yu

In this paper, we introduce median sampling as a noise handling strategy into EAs, which uses the median of the multiple evaluations to approximate the true fitness instead of the mean.

Key Ingredients of Self-Driving Cars

no code implementations7 Jun 2019 Rui Fan, Jianhao Jiao, Haoyang Ye, Yang Yu, Ioannis Pitas, Ming Liu

Over the past decade, many research articles have been published in the area of autonomous driving.

Autonomous Driving Self-Driving Cars

Knowledge-augmented Column Networks: Guiding Deep Learning with Advice

no code implementations31 May 2019 Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan

Recently, deep models have had considerable success in several tasks, especially with low-level representations.

Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit

no code implementations31 May 2019 Yi-Qi Hu, Yang Yu, Jun-Da Liao

We show theoretically that the ER-UCB has a regret upper bound $O\left(K \ln n\right)$ with independent feedbacks, which is as efficient as the classical UCB bandit.


Computer-aided Detection of Squamous Carcinoma of the Cervix in Whole Slide Images

no code implementations27 May 2019 Ye Tian, Li Yang, Wei Wang, Jing Zhang, Qing Tang, Mili Ji, Yang Yu, Yu Li, Hong Yang, Airong Qian

Traditionally, the most indispensable diagnosis of cervix squamous carcinoma is histopathological assessment which is achieved under microscope by pathologist.

whole slide images

Automatic Calibration of Multiple 3D LiDARs in Urban Environments

no code implementations13 May 2019 Jianhao Jiao, Yang Yu, Qinghai Liao, Haoyang Ye, Ming Liu

Multiple LiDARs have progressively emerged on autonomous vehicles for rendering a wide field of view and dense measurements.

Autonomous Vehicles Translation

Human-Guided Column Networks: Augmenting Deep Learning with Advice

no code implementations ICLR 2019 Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan

While extremely successful in several applications, especially with low-level representations; sparse, noisy samples and structured domains (with multiple objects and interactions) are some of the open challenges in most deep models.

A Novel Dual-Lidar Calibration Algorithm Using Planar Surfaces

no code implementations27 Apr 2019 Jianhao Jiao, Qinghai Liao, Yilong Zhu, Tianyu Liu, Yang Yu, Rui Fan, Lujia Wang, Ming Liu

Multiple lidars are prevalently used on mobile vehicles for rendering a broad view to enhance the performance of localization and perception systems.


Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice

no code implementations15 Apr 2019 Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan

Recently, deep models have been successfully applied in several applications, especially with low-level representations.

PointIT: A Fast Tracking Framework Based on 3D Instance Segmentation

no code implementations18 Feb 2019 Yu-An Wang, Yang Yu, Ming Liu

Finally, we extend the Sort algorithm with this instance framework to realize tracking in the 3D LiDAR point cloud data.

3D Instance Segmentation Semantic Segmentation

Tuplemax Loss for Language Identification

1 code implementation29 Nov 2018 Li Wan, Prashant Sridhar, Yang Yu, Quan Wang, Ignacio Lopez Moreno

In many scenarios of a language identification task, the user will specify a small set of languages which he/she can speak instead of a large set of all possible languages.

Language Identification

Day-to-Day Dynamic Traffic Assignment with Imperfect Information, Bounded Rationality and Information Sharing

1 code implementation26 Nov 2018 Yang Yu, Ke Han, Washington Ochieng

These two variants, serving as based models, are further extended with two features: bounded rationality (BR) and information sharing.

Physics and Society Optimization and Control

Taking Human out of Learning Applications: A Survey on Automated Machine Learning

1 code implementation31 Oct 2018 Quanming Yao, Mengshuo Wang, Yuqiang Chen, Wenyuan Dai, Yu-Feng Li, Wei-Wei Tu, Qiang Yang, Yang Yu

We hope this survey can serve as not only an insightful guideline for AutoML beginners but also an inspiration for future research.


Analysis of Noisy Evolutionary Optimization When Sampling Fails

no code implementations11 Oct 2018 Chao Qian, Chao Bian, Yang Yu, Ke Tang, Xin Yao

In this paper, we first investigate the effect of sample size from a theoretical perspective.

Exploration by Uncertainty in Reward Space

no code implementations27 Sep 2018 Wei-Yang Qu, Yang Yu, Tang-Jie Lv, Ying-Feng Chen, Chang-Jie Fan

There are two policies in this approach, the exploration policy is used for exploratory sampling in the environment, then the benchmark policy try to update by the data proven by the exploration policy.

Atari Games Efficient Exploration +1

Multi-Layered Gradient Boosting Decision Trees

1 code implementation NeurIPS 2018 Ji Feng, Yang Yu, Zhi-Hua Zhou

Multi-layered representation is believed to be the key ingredient of deep neural networks especially in cognitive tasks like computer vision.

Representation Learning

Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application

1 code implementation2 Mar 2018 Yujing Hu, Qing Da, An-Xiang Zeng, Yang Yu, Yinghui Xu

For better utilizing the correlation between different ranking steps, in this paper, we propose to use reinforcement learning (RL) to learn an optimal ranking policy which maximizes the expected accumulative rewards in a search session.

Decision Making Learning-To-Rank +1

Tunneling Neural Perception and Logic Reasoning through Abductive Learning

1 code implementation4 Feb 2018 Wang-Zhou Dai, Qiu-Ling Xu, Yang Yu, Zhi-Hua Zhou

Perception and reasoning are basic human abilities that are seamlessly connected as part of human intelligence.

ZOOpt: Toolbox for Derivative-Free Optimization

2 code implementations31 Dec 2017 Yu-Ren Liu, Yi-Qi Hu, Hong Qian, Yang Yu, Chao Qian

Recent advances of derivative-free optimization allow efficient approximating the global optimal solutions of sophisticated functions, such as functions with many local optima, non-differentiable and non-continuous functions.

Subset Selection under Noise

no code implementations NeurIPS 2017 Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, Zhi-Hua Zhou

The problem of selecting the best $k$-element subset from a universe is involved in many applications.

Maximizing Non-monotone/Non-submodular Functions by Multi-objective Evolutionary Algorithms

no code implementations20 Nov 2017 Chao Qian, Yang Yu, Ke Tang, Xin Yao, Zhi-Hua Zhou

To provide a general theoretical explanation of the behavior of EAs, it is desirable to study the performance of EAs on a general class of combinatorial optimization problems.

Combinatorial Optimization

Open-Category Classification by Adversarial Sample Generation

no code implementations24 May 2017 Yang Yu, Wei-Yang Qu, Nan Li, Zimin Guo

ASG generates positive and negative samples of seen categories in the unsupervised manner via an adversarial learning strategy.

Classification General Classification

End-to-End Answer Chunk Extraction and Ranking for Reading Comprehension

no code implementations31 Oct 2016 Yang Yu, Wei zhang, Kazi Hasan, Mo Yu, Bing Xiang, Bo-Wen Zhou

This paper proposes dynamic chunk reader (DCR), an end-to-end neural reading comprehension (RC) model that is able to extract and rank a set of answer candidates from a given document to answer questions.

Question Answering Reading Comprehension

A Lower Bound Analysis of Population-based Evolutionary Algorithms for Pseudo-Boolean Functions

no code implementations10 Jun 2016 Chao Qian, Yang Yu, Zhi-Hua Zhou

Our results imply that the increase of population size, while usually desired in practice, bears the risk of increasing the lower bound of the running time and thus should be carefully considered.

Subset Selection by Pareto Optimization

no code implementations NeurIPS 2015 Chao Qian, Yang Yu, Zhi-Hua Zhou

Selecting the optimal subset from a large set of variables is a fundamental problem in various learning tasks such as feature selection, sparse regression, dictionary learning, etc.

Dictionary Learning

Empirical Study on Deep Learning Models for Question Answering

no code implementations26 Oct 2015 Yang Yu, Wei zhang, Chung-Wei Hang, Bing Xiang, Bo-Wen Zhou

In this paper we explore deep learning models with memory component or attention mechanism for question answering task.

Machine Translation Question Answering +1

Structured Memory for Neural Turing Machines

no code implementations14 Oct 2015 Wei Zhang, Yang Yu, Bo-Wen Zhou

Neural Turing Machines (NTM) contain memory component that simulates "working memory" in the brain to store and retrieve information to ease simple algorithms learning.

Recognizing Extended Spatiotemporal Expressions by Actively Trained Average Perceptron Ensembles

no code implementations19 Aug 2015 Wei Zhang, Yang Yu, Osho Gupta, Judith Gelernter

We collected and annotated data set by querying commercial web searches API with such spatiotemporal expressions as were missed by state-of-the- art parsers.

Active Learning Ensemble Learning

The Sampling-and-Learning Framework: A Statistical View of Evolutionary Algorithms

no code implementations24 Jan 2014 Yang Yu, Hong Qian

By summarizing a large range of EAs into the sampling-and-learning framework, we show that the framework directly admits a general analysis on the probable-absolute-approximate (PAA) query complexity.

General Classification Learning Theory

Analyzing Evolutionary Optimization in Noisy Environments

no code implementations20 Nov 2013 Chao Qian, Yang Yu, Zhi-Hua Zhou

On a representative problem where the noise has a strong negative effect, we examine two commonly employed mechanisms in EAs dealing with noise, the re-evaluation and the threshold selection strategies.

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