no code implementations • 27 Oct 2023 • Wentao Guo, Andrew Wang, Bradon Thymes, Thorsten Joachims
We introduce the problem of ranking with slot constraints, which can be used to model a wide range of application problems -- from college admission with limited slots for different majors, to composing a stratified cohort of eligible participants in a medical trial.
1 code implementation • 27 Sep 2023 • Lin Yao, Wentao Guo, Zhen Wang, Shang Xiang, Wentan Liu, Guolin Ke
Single-step retrosynthesis (SSR) in organic chemistry is increasingly benefiting from deep learning (DL) techniques in computer-aided synthesis design.
Ranked #3 on Single-step retrosynthesis on USPTO-50k
no code implementations • 9 Jul 2023 • Yann Hicke, Abhishek Masand, Wentao Guo, Tushaar Gangavarapu
(Tack et al., 2023) organized the shared task hosted by the 18th Workshop on Innovative Use of NLP for Building Educational Applications on generation of teacher language in educational dialogues.
1 code implementation • NeurIPS 2023 • A. Feder Cooper, Wentao Guo, Khiem Pham, Tiancheng Yuan, Charlie F. Ruan, Yucheng Lu, Christopher De Sa
Recent research on online Gradient Balancing (GraB) has revealed that there exist permutation-based example orderings for SGD that are guaranteed to outperform random reshuffling (RR).
no code implementations • 26 Nov 2022 • Wentao Guo, Charlie Ruan, Claire Zhou
Photo Rater is a computer vision project that uses neural networks to help photographers select the best photo among those that are taken based on the same scene.
1 code implementation • 18 Jul 2022 • Tao Yu, Wentao Guo, Jianan Canal Li, Tiancheng Yuan, Christopher De Sa
In this paper, we introduce MCTensor, a library based on PyTorch for providing general-purpose and high-precision arithmetic for DL training.
1 code implementation • 29 Jun 2022 • Jianan Canal Li, Yimeng Zeng, Wentao Guo
We propose cKAM, cyclical Kernel Adaptive Metropolis, which incorporates a cyclical stepsize scheme to allow control for exploration and sampling.
2 code implementations • 22 May 2022 • Yucheng Lu, Wentao Guo, Christopher De Sa
To reduce the memory overhead, we leverage discrepancy minimization theory to propose an online Gradient Balancing algorithm (GraB) that enjoys the same rate as herding, while reducing the memory usage from $O(nd)$ to just $O(d)$ and computation from $O(n^2)$ to $O(n)$, where $d$ denotes the model dimension.
no code implementations • 14 Aug 2017 • Yan Yan, Wentao Guo, Meng Zhao, Jinghe Hu, Weipeng P. Yan
With the transition from people's traditional `brick-and-mortar' shopping to online mobile shopping patterns in web 2. 0 $\mathit{era}$, the recommender system plays a critical role in E-Commerce and E-Retails.