Search Results for author: Haiyan Yin

Found 10 papers, 1 papers with code

Learning to Selectively Learn for Weakly Supervised Paraphrase Generation with Model-based Reinforcement Learning

no code implementations NAACL 2022 Haiyan Yin, Dingcheng Li, Ping Li

In this paper, we propose a new weakly supervised paraphrase generation approach that extends the success of a recent work that leverages reinforcement learning for effective model training with data selection.

Model-based Reinforcement Learning Paraphrase Generation

Crowd-level Abnormal Behavior Detection via Multi-scale Motion Consistency Learning

no code implementations1 Dec 2022 Linbo Luo, Yuanjing Li, Haiyan Yin, Shangwei Xie, Ruimin Hu, Wentong Cai

In this paper, we present a systematic study to tackle the important problem of VAD for CABs with a novel crowd motion learning framework, multi-scale motion consistency network (MSMC-Net).

Anomaly Detection Video Anomaly Detection

Causal Discovery with Flow-based Conditional Density Estimation

1 code implementation ICDM 21 2021 Shaogang Ren, Haiyan Yin, Mingming Sun, Ping Li

Then we formulate a novel evaluation metric to infer the scores for each potential causal direction based on the variance of the conditional density estimation.

Causal Discovery Density Estimation

Mitigating Forgetting in Online Continual Learning with Neuron Calibration

no code implementations NeurIPS 2021 Haiyan Yin, Peng Yang, Ping Li

Though recent studies have achieved remarkable progress in improving the online continual learning performance empowered by the deep neural networks-based models, many of today's approaches still suffer a lot from catastrophic forgetting, a persistent challenge for continual learning.

Continual Learning

Mitigating Forgetting in Online Continual Learning with Neuron Calibration

no code implementations NeurIPS 2021 Haiyan Yin, Peng Yang, Ping Li

Though recent studies have achieved remarkable progress in improving the online continual learning performance empowered by the deep neural networks-based models, many of today's approaches still suffer a lot from catastrophic forgetting, a persistent challenge for continual learning.

Continual Learning

CASA: Bridging the Gap between Policy Improvement and Policy Evaluation with Conflict Averse Policy Iteration

no code implementations9 May 2021 Changnan Xiao, Haosen Shi, Jiajun Fan, Shihong Deng, Haiyan Yin

We study the problem of model-free reinforcement learning, which is often solved following the principle of Generalized Policy Iteration (GPI).

Atari Games

Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation

no code implementations12 Mar 2020 Haiyan Yin, Dingcheng Li, Xu Li, Ping Li

To this end, we introduce a cooperative training paradigm, where a language model is cooperatively trained with the generator and we utilize the language model to efficiently shape the data distribution of the generator against mode collapse.

Adversarial Text Language Modelling +2

Sequence-level Intrinsic Exploration Model for Partially Observable Domains

no code implementations25 Sep 2019 Haiyan Yin, Jianda Chen, Sinno Jialin Pan

First, we propose a new reasoning paradigm to infer the novelty for the partially observable states, which is built upon forward dynamics prediction.

reinforcement-learning Reinforcement Learning (RL)

Hashing over Predicted Future Frames for Informed Exploration of Deep Reinforcement Learning

no code implementations3 Jul 2017 Haiyan Yin, Jianda Chen, Sinno Jialin Pan

In deep reinforcement learning (RL) tasks, an efficient exploration mechanism should be able to encourage an agent to take actions that lead to less frequent states which may yield higher accumulative future return.

Efficient Exploration reinforcement-learning +1

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