no code implementations • 13 Jan 2025 • Yuchen Lu, Kun Fang
Quantum relative entropy, a quantum generalization of the well-known Kullback-Leibler divergence, serves as a fundamental measure of the distinguishability between quantum states and plays a pivotal role in quantum information science.
no code implementations • 27 Nov 2023 • Zherui Chen, Yuchen Lu, Hao Wang, Yizhou Liu, Tongyang Li
Finally, based on the observations when comparing QLD with classical Fokker-Plank-Smoluchowski equation, we propose a time-dependent QLD by making temperature and $\hbar$ time-dependent parameters, which can be theoretically proven to converge better than the time-independent case and also outperforms a series of state-of-the-art quantum and classical optimization algorithms in many non-convex landscapes.
no code implementations • 17 Apr 2023 • Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao, Chuang Gan
To address this challenge, we propose a new framework, called Hyper-Decision Transformer (HDT), that can generalize to novel tasks from a handful of demonstrations in a data- and parameter-efficient manner.
no code implementations • 10 Dec 2022 • Siddharth Verma, Yuchen Lu, Rui Hou, Hanchao Yu, Nicolas Ballas, Madian Khabsa, Amjad Almahairi
Masked Language Modeling (MLM) has proven to be an essential component of Vision-Language (VL) pretraining.
no code implementations • 27 Jun 2022 • Mengdi Xu, Yikang Shen, Shun Zhang, Yuchen Lu, Ding Zhao, Joshua B. Tenenbaum, Chuang Gan
Humans can leverage prior experience and learn novel tasks from a handful of demonstrations.
no code implementations • 2 Jun 2022 • Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron Courville, Alessandro Sordoni
We address the problem of evaluating the quality of self-supervised learning (SSL) models without access to supervised labels, while being agnostic to the architecture, learning algorithm or data manipulation used during training.
no code implementations • 29 Sep 2021 • Yuchen Lu, Zhen Liu, Alessandro Sordoni, Aristide Baratin, Romain Laroche, Aaron Courville
In this work, we argue that representations induced by self-supervised learning (SSL) methods should both be expressive and learnable.
no code implementations • 29 Sep 2021 • Siyuan Zhou, Yikang Shen, Yuchen Lu, Aaron Courville, Joshua B. Tenenbaum, Chuang Gan
With the isolation of information and the synchronous calling mechanism, we can impose a division of works between the controller and options in an end-to-end training regime.
no code implementations • ICLR 2021 • Ankit Vani, Max Schwarzer, Yuchen Lu, Eeshan Dhekane, Aaron Courville
Although neural module networks have an architectural bias towards compositionality, they require gold standard layouts to generalize systematically in practice.
no code implementations • 19 Mar 2021 • Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron Courville, Joshua B. Tenenbaum, Chuang Gan
The discovered subtask hierarchy could be used to perform task decomposition, recovering the subtask boundaries in an unstruc-tured demonstration.
no code implementations • ICLR 2021 • Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron Courville, Joshua B. Tenenbaum, Chuang Gan
Many complex real-world tasks are composed of several levels of sub-tasks.
no code implementations • EMNLP 2020 • Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron Courville
Language drift has been one of the major obstacles to train language models through interaction.
no code implementations • ICML 2020 • Yuchen Lu, Soumye Singhal, Florian Strub, Olivier Pietquin, Aaron Courville
At each time step, the teacher is created by copying the student agent, before being finetuned to maximize task completion.
no code implementations • 20 Mar 2020 • Xuan Li, Yuchen Lu, Christian Desrosiers, Xue Liu
In this paper, we study the problem of out-of-distribution detection in skin disease images.
no code implementations • NeurIPS 2019 • Philip Paquette, Yuchen Lu, Seton Steven Bocco, Max Smith, Satya O.-G., Jonathan K. Kummerfeld, Joelle Pineau, Satinder Singh, Aaron C. Courville
Diplomacy is a seven-player non-stochastic, non-cooperative game, where agents acquire resources through a mix of teamwork and betrayal.
no code implementations • 2 Oct 2019 • Xuan Li, Yuchen Lu, Peng Xu, Jizong Peng, Christian Desrosiers, Xue Liu
In this paper, we study the problem of image recognition with non-differentiable constraints.
1 code implementation • 4 Sep 2019 • Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Satinder Singh, Joelle Pineau, Aaron Courville
Diplomacy is a seven-player non-stochastic, non-cooperative game, where agents acquire resources through a mix of teamwork and betrayal.
no code implementations • 3 Jul 2018 • Yuchen Lu, Peng Xu
If we focus on specific diseases, the model is able to detect melanoma with 0. 864 AUCROC and detect actinic keratosis with 0. 872 AUCROC, even if it only sees the images of nevus.
no code implementations • ICLR 2018 • Tong Che, Yuchen Lu, George Tucker, Surya Bhupatiraju, Shane Gu, Sergey Levine, Yoshua Bengio
Model-free deep reinforcement learning algorithms are able to successfully solve a wide range of continuous control tasks, but typically require many on-policy samples to achieve good performance.