Haonan Yu

CoRR, 2024

2023

Policy Expansion for Bridging Offline-to-Online Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Do You Need the Entropy Reward (in Practice)?

[BibT_eX]

[DOI]

CoRR, 2022

Towards Safe Reinforcement Learning with a Safety Editor Policy.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generative Planning for Temporally Coordinated Exploration in Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Data Mining Series Experiment Design and OJ System Development Based on R Language.

[BibT_eX]

[DOI]

Proceedings of the Computer Science and Education - 17th International Conference, 2022

2021

Interactive Hepatic Parenchymal Transection Simulation with Haptic Feedback.

[BibT_eX]

[DOI]

Virtual Real. Intell. Hardw., 2021

TASAC: Temporally Abstract Soft Actor-Critic for Continuous Control.

[BibT_eX]

[DOI]

CoRR, 2021

MetaView: Few-shot Active Object Recognition.

[BibT_eX]

[DOI]

CoRR, 2021

TAAC: Temporally Abstract Actor-Critic for Continuous Control.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Hierarchical Reinforcement Learning by Discovering Intrinsic Options.

[BibT_eX]

[DOI]

Jesse Zhang

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

QTMS: A quadratic time complexity topology-aware process mapping method for large-scale parallel applications on shared HPC system.

[BibT_eX]

[DOI]

Parallel Comput., 2020

Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Why Build an Assistant in Minecraft?

[BibT_eX]

[DOI]

CoRR, 2019

CraftAssist: A Framework for Dialogue-enabled Interactive Agents.

[BibT_eX]

[DOI]

CoRR, 2019

EPNAS: Efficient Progressive Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2019

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Order-Aware Generative Modeling Using the 3D-Craft Dataset.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Driving Under the Influence (of Language).

[BibT_eX]

[DOI]

Scott Alan Bronikowski

IEEE Trans. Neural Networks Learn. Syst., 2018

Resource-Efficient Neural Architect.

[BibT_eX]

[DOI]

CoRR, 2018

Interactive Grounded Language Acquisition and Generalization in a 2D World.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Guided Feature Transformation (GFT): A Neural Language Grounding Module for Embodied Agents.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Interactive Language Acquisition with One-shot Visual Concept Learning through a Conversational Game.

[BibT_eX]

[DOI]

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Sentence Directed Video Object Codiscovery.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2017

Listen, Interact and Talk: Learning to Speak via Interaction.

[BibT_eX]

[DOI]

CoRR, 2017

A Deep Compositional Framework for Human-like Language Acquisition in Virtual Environment.

[BibT_eX]

[DOI]

CoRR, 2017

2016

Collecting and annotating the large continuous action dataset.

[BibT_eX]

[DOI]

Mach. Vis. Appl., 2016

Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

A Compositional Framework for Grounding Language Inference, Generation, and Acquisition in Video.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2015

Sentence Directed Video Object Codetection.

[BibT_eX]

[DOI]

CoRR, 2015

Robot Language Learning, Generation, and Comprehension.

[BibT_eX]

[DOI]

Scott Alan Bronikowski

CoRR, 2015

Learning to Describe Video with Weak Supervision by Exploiting Negative Sentential Information.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

A Faster Method for Tracking and Scoring Videos Corresponding to Sentences.

[BibT_eX]

[DOI]

CoRR, 2014

2013

Discriminative Training: Learning to Describe Video with Sentences, from Video Described with Sentences.

[BibT_eX]

[DOI]

CoRR, 2013

Recognize Human Activities from Partially Observed Videos.

[BibT_eX]

[DOI]

Yu Cao

Andrei Barbu

Siddharth Narayanaswamy

Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

Grounded Language Learning from Video Described with Sentences.

[BibT_eX]

[DOI]