no code implementations • 2 Nov 2023 • Linan Zheng, Jiale Chen, Pengsheng Liu, Guangfa Zhang, Jinyun Fang
We observe that the model can generate expressive embeddings for warm users with relatively more interactions.
no code implementations • 23 Sep 2023 • Zihua Si, Zhongxiang Sun, Jiale Chen, Guozhang Chen, Xiaoxue Zang, Kai Zheng, Yang song, Xiao Zhang, Jun Xu
To obtain efficiency and effectiveness, this paper introduces a generative retrieval framework, namely SEATER, which learns SEmAntic Tree-structured item identifiERs via contrastive learning.
1 code implementation • 27 Jul 2023 • Lingdong Kong, Yaru Niu, Shaoyuan Xie, Hanjiang Hu, Lai Xing Ng, Benoit R. Cottereau, Ding Zhao, Liangjun Zhang, Hesheng Wang, Wei Tsang Ooi, Ruijie Zhu, Ziyang Song, Li Liu, Tianzhu Zhang, Jun Yu, Mohan Jing, Pengwei Li, Xiaohua Qi, Cheng Jin, Yingfeng Chen, Jie Hou, Jie Zhang, Zhen Kan, Qiang Ling, Liang Peng, Minglei Li, Di Xu, Changpeng Yang, Yuanqi Yao, Gang Wu, Jian Kuai, Xianming Liu, Junjun Jiang, Jiamian Huang, Baojun Li, Jiale Chen, Shuang Zhang, Sun Ao, Zhenyu Li, Runze Chen, Haiyong Luo, Fang Zhao, Jingze Yu
In this paper, we summarize the winning solutions from the RoboDepth Challenge -- an academic competition designed to facilitate and advance robust OoD depth estimation.
no code implementations • 13 Apr 2023 • Jiale Chen, Jason Hartline, Onno Zoeter
In a randomized exam, each student is asked a small number of random questions from a large question bank.
no code implementations • 24 Feb 2021 • Jiale Chen, Yuqing Kong, Yuxuan Lu
With this assumption, we propose a new definition for uninformative feedback and correspondingly design a family of evaluation metrics, called f-variety, for group-level feedback which can 1) distinguish informative feedback and uninformative feedback (separation) even if their statistics are both uniform and 2) decrease as the ratio of uninformative respondents increases (monotonicity).
Computer Science and Game Theory
no code implementations • 4 Mar 2020 • Jiale Chen, Xu Tan, Chaowei Shan, Sen Liu, Zhibo Chen
This paper introduces VESR-Net, a method for video enhancement and super-resolution (VESR).
no code implementations • 25 Dec 2019 • Xu Tan, Yichong Leng, Jiale Chen, Yi Ren, Tao Qin, Tie-Yan Liu
Multilingual neural machine translation (NMT) has recently been investigated from different aspects (e. g., pivot translation, zero-shot translation, fine-tuning, or training from scratch) and in different settings (e. g., rich resource and low resource, one-to-many, and many-to-one translation).
no code implementations • IJCNLP 2019 • Xu Tan, Jiale Chen, Di He, Yingce Xia, Tao Qin, Tie-Yan Liu
We study two methods for language clustering: (1) using prior knowledge, where we cluster languages according to language family, and (2) using language embedding, in which we represent each language by an embedding vector and cluster them in the embedding space.
no code implementations • 17 Aug 2019 • Tianyu He, Jiale Chen, Xu Tan, Tao Qin
Neural machine translation on low-resource language is challenging due to the lack of bilingual sentence pairs.
2 code implementations • 24 Jul 2019 • Zongyu Guo, Zhibo Chen, Tao Yu, Jiale Chen, Sen Liu
Recently, learning-based algorithms for image inpainting achieve remarkable progress dealing with squared or irregular holes.
1 code implementation • 3 Mar 2019 • Zhizheng Zhang, Jiale Chen, Zhibo Chen, Weiping Li
Not limited to the control tasks in computationally complex environments, AE-DDPG also achieves higher rewards and 2- to 4-fold improvement in sample efficiency on average compared to other variants of DDPG in MuJoCo environments.
2 code implementations • 2 Apr 2018 • Łukasz Kidziński, Sharada Prasanna Mohanty, Carmichael Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko, Adam Stelmaszczyk, Piotr Jarosik, Mikhail Pavlov, Sergey Kolesnikov, Sergey Plis, Zhibo Chen, Zhizheng Zhang, Jiale Chen, Jun Shi, Zhuobin Zheng, Chun Yuan, Zhihui Lin, Henryk Michalewski, Piotr Miłoś, Błażej Osiński, Andrew Melnik, Malte Schilling, Helge Ritter, Sean Carroll, Jennifer Hicks, Sergey Levine, Marcel Salathé, Scott Delp
In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle course.