no code implementations • ICML 2020 • Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel
We experiment with three structured bandit problems: cascading bandits, online learning to rank in the position-based model, and rank-1 bandits.
no code implementations • ACL 2022 • Rui Wang, Tong Yu, Handong Zhao, Sungchul Kim, Subrata Mitra, Ruiyi Zhang, Ricardo Henao
In this work, we study a more challenging but practical problem, i. e., few-shot class-incremental learning for NER, where an NER model is trained with only few labeled samples of the new classes, without forgetting knowledge of the old ones.
no code implementations • 24 Apr 2024 • Yu Xia, Rui Wang, Xu Liu, Mingyan Li, Tong Yu, Xiang Chen, Julian McAuley, Shuai Li
Chain-of-Thought (CoT) has been a widely adopted prompting method, eliciting impressive reasoning abilities of Large Language Models (LLMs).
no code implementations • 4 Apr 2024 • Chengkai Huang, Rui Wang, Kaige Xie, Tong Yu, Lina Yao
Despite their great success, the knowledge provided by the retrieval process is not always useful for improving the model prediction, since in some samples LLMs may already be quite knowledgeable and thus be able to answer the question correctly without retrieval.
no code implementations • 2 Apr 2024 • Yu Xia, Xu Liu, Tong Yu, Sungchul Kim, Ryan A. Rossi, Anup Rao, Tung Mai, Shuai Li
Large Language Models (LLMs) have shown propensity to generate hallucinated outputs, i. e., texts that are factually incorrect or unsupported.
no code implementations • 26 Mar 2024 • Ting-Yao Hsu, Chieh-Yang Huang, Shih-Hong Huang, Ryan Rossi, Sungchul Kim, Tong Yu, C. Lee Giles, Ting-Hao K. Huang
Crafting effective captions for figures is important.
no code implementations • 26 Mar 2024 • Xiaocong Chen, Siyu Wang, Tong Yu, Lina Yao
Offline reinforcement learning (RL) presents distinct challenges as it relies solely on observational data.
no code implementations • 14 Mar 2024 • Xiaoyu Liu, Paiheng Xu, Junda Wu, Jiaxin Yuan, Yifan Yang, YuHang Zhou, Fuxiao Liu, Tianrui Guan, Haoliang Wang, Tong Yu, Julian McAuley, Wei Ai, Furong Huang
Causal inference has shown potential in enhancing the predictive accuracy, fairness, robustness, and explainability of Natural Language Processing (NLP) models by capturing causal relationships among variables.
no code implementations • 11 Mar 2024 • Yu Xia, Fang Kong, Tong Yu, Liya Guo, Ryan A. Rossi, Sungchul Kim, Shuai Li
In this paper, we propose a time-increasing bandit algorithm TI-UCB, which effectively predicts the increase of model performances due to finetuning and efficiently balances exploration and exploitation in model selection.
no code implementations • 11 Mar 2024 • Junda Wu, Cheng-Chun Chang, Tong Yu, Zhankui He, Jianing Wang, Yupeng Hou, Julian McAuley
Based on the retrieved user-item interactions, the LLM can analyze shared and distinct preferences among users, and summarize the patterns indicating which types of users would be attracted by certain items.
no code implementations • 22 Feb 2024 • Younghun Lee, Sungchul Kim, Tong Yu, Ryan A. Rossi, Xiang Chen
The model learns to reduce the input context using On-Policy Reinforcement Learning and aims to improve the reasoning performance of a fixed LLM.
no code implementations • 17 Feb 2024 • Chengkai Huang, Tong Yu, Kaige Xie, Shuai Zhang, Lina Yao, Julian McAuley
Recently, Foundation Models (FMs), with their extensive knowledge bases and complex architectures, have offered unique opportunities within the realm of recommender systems (RSs).
no code implementations • 3 Feb 2024 • Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, Md Mehrab Tanjim, Tong Yu, Hanieh Deilamsalehy, Ruiyi Zhang, Sungchul Kim, Franck Dernoncourt
Large language models (LLMs) have shown remarkable advances in language generation and understanding but are also prone to exhibiting harmful social biases.
1 code implementation • 28 Jan 2024 • Yujian Liu, Jiabao Ji, Tong Yu, Ryan Rossi, Sungchul Kim, Handong Zhao, Ritwik Sinha, Yang Zhang, Shiyu Chang
Table question answering is a popular task that assesses a model's ability to understand and interact with structured data.
1 code implementation • 11 Jan 2024 • Zhihui Xie, Handong Zhao, Tong Yu, Shuai Li
While these results are promising, follow-up works found that, within the multilingual embedding spaces, there exists strong language identity information which hinders the expression of linguistic factors shared across languages.
no code implementations • 4 Jan 2024 • Zeyu Li, Jingsheng Gao, Tong Yu, Suncheng Xiang, Jiacheng Ruan, Ting Liu, Yuzhuo Fu
Existing research on audio classification faces challenges in recognizing attributes of passive underwater vessel scenarios and lacks well-annotated datasets due to data privacy concerns.
no code implementations • 29 Nov 2023 • Puja Trivedi, Ryan Rossi, David Arbour, Tong Yu, Franck Dernoncourt, Sungchul Kim, Nedim Lipka, Namyong Park, Nesreen K. Ahmed, Danai Koutra
Most real-world networks are noisy and incomplete samples from an unknown target distribution.
2 code implementations • 27 Nov 2023 • Shaohua Wu, Xudong Zhao, Shenling Wang, Jiangang Luo, Lingjun Li, Xi Chen, Bing Zhao, Wei Wang, Tong Yu, Rongguo Zhang, Jiahua Zhang, Chao Wang
In this work, we develop and release Yuan 2. 0, a series of large language models with parameters ranging from 2. 1 billion to 102. 6 billion.
no code implementations • 25 Oct 2023 • Zhendong Chu, Ruiyi Zhang, Tong Yu, Rajiv Jain, Vlad I Morariu, Jiuxiang Gu, Ani Nenkova
To achieve state-of-the-art performance, one still needs to train NER models on large-scale, high-quality annotated data, an asset that is both costly and time-intensive to accumulate.
no code implementations • 20 Oct 2023 • Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, Chao Zhang
It formulates the entire action space as a decision tree, where each node represents a possible API function call involved in a solution plan.
1 code implementation • 2 Sep 2023 • Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, Md Mehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, Nesreen K. Ahmed
Rapid advancements of large language models (LLMs) have enabled the processing, understanding, and generation of human-like text, with increasing integration into systems that touch our social sphere.
1 code implementation • 27 Jul 2023 • Kun Yuan, Vinkle Srivastav, Tong Yu, Joel L. Lavanchy, Pietro Mascagni, Nassir Navab, Nicolas Padoy
SurgVLP constructs a new contrastive learning objective to align video clip embeddings with the corresponding multiple text embeddings by bringing them together within a joint latent space.
1 code implementation • 20 Jul 2023 • Ashish Singh, Prateek Agarwal, Zixuan Huang, Arpita Singh, Tong Yu, Sungchul Kim, Victor Bursztyn, Nikos Vlassis, Ryan A. Rossi
Captions are crucial for understanding scientific visualizations and documents.
no code implementations • 8 Jul 2023 • April Chen, Ryan A. Rossi, Namyong Park, Puja Trivedi, Yu Wang, Tong Yu, Sungchul Kim, Franck Dernoncourt, Nesreen K. Ahmed
In this article, we examine and categorize fairness techniques for improving the fairness of GNNs.
1 code implementation • NeurIPS 2023 • Jian Chen, Ruiyi Zhang, Tong Yu, Rohan Sharma, Zhiqiang Xu, Tong Sun, Changyou Chen
Remarkably, by incorporating conditional information from the powerful CLIP model, our method can boost the current SOTA accuracy by 10-20 absolute points in many cases.
Ranked #1 on Image Classification on Food-101N (using extra training data)
no code implementations • 20 May 2023 • Kaige Xie, Tong Yu, Haoliang Wang, Junda Wu, Handong Zhao, Ruiyi Zhang, Kanak Mahadik, Ani Nenkova, Mark Riedl
In this paper, we focus on improving the prompt transfer from dialogue state tracking to dialogue summarization and propose Skeleton-Assisted Prompt Transfer (SAPT), which leverages skeleton generation as extra supervision that functions as a medium connecting the distinct source and target task and resulting in the model's better consumption of dialogue state information.
1 code implementation • 9 May 2023 • Jianyi Zhang, Saeed Vahidian, Martin Kuo, Chunyuan Li, Ruiyi Zhang, Tong Yu, Yufan Zhou, Guoyin Wang, Yiran Chen
This repository offers a foundational framework for exploring federated fine-tuning of LLMs using heterogeneous instructions across diverse categories.
no code implementations • 26 Apr 2023 • Shuai Li, Zhao Song, Yu Xia, Tong Yu, Tianyi Zhou
Large language models (LLMs) are known for their exceptional performance in natural language processing, making them highly effective in many human life-related or even job-related tasks.
no code implementations • 28 Mar 2023 • Rashmi Ranjan Bhuyan, Adel Javanmard, Sungchul Kim, Gourab Mukherjee, Ryan A. Rossi, Tong Yu, Handong Zhao
We consider dynamic pricing strategies in a streamed longitudinal data set-up where the objective is to maximize, over time, the cumulative profit across a large number of customer segments.
no code implementations • 21 Feb 2023 • Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez, Tong Yu, Pietro Mascagni, Didier Mutter, Jacques Marescaux, Paolo Fiorini, Nicolas Padoy
In this work, we propose to use coarser and easier-to-annotate activity labels, namely phases, as weak supervision to learn step recognition with fewer step annotated videos.
2 code implementations • 13 Feb 2023 • Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma, Aditya Murali, Deepak Alapatt, Armine Vardazaryan, Kun Yuan, Jonas Hajek, Wolfgang Reiter, Amine Yamlahi, Finn-Henri Smidt, Xiaoyang Zou, Guoyan Zheng, Bruno Oliveira, Helena R. Torres, Satoshi Kondo, Satoshi Kasai, Felix Holm, Ege Özsoy, Shuangchun Gui, Han Li, Sista Raviteja, Rachana Sathish, Pranav Poudel, Binod Bhattarai, Ziheng Wang, Guo Rui, Melanie Schellenberg, João L. Vilaça, Tobias Czempiel, Zhenkun Wang, Debdoot Sheet, Shrawan Kumar Thapa, Max Berniker, Patrick Godau, Pedro Morais, Sudarshan Regmi, Thuy Nuong Tran, Jaime Fonseca, Jan-Hinrich Nölke, Estevão Lima, Eduard Vazquez, Lena Maier-Hein, Nassir Navab, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Didier Mutter, Nicolas Padoy
This paper presents the CholecTriplet2022 challenge, which extends surgical action triplet modeling from recognition to detection.
Ranked #1 on Action Triplet Detection on CholecT50 (Challenge)
1 code implementation • CVPR 2023 • Qiucheng Wu, Yujian Liu, Handong Zhao, Ajinkya Kale, Trung Bui, Tong Yu, Zhe Lin, Yang Zhang, Shiyu Chang
Based on this finding, we further propose a simple, light-weight image editing algorithm where the mixing weights of the two text embeddings are optimized for style matching and content preservation.
no code implementations • 12 Dec 2022 • Shaddy Garg, Subrata Mitra, Tong Yu, Yash Gadhia, Arjun Kashettiwar
Exploratory data analytics (EDA) is a sequential decision making process where analysts choose subsequent queries that might lead to some interesting insights based on the previous queries and corresponding results.
no code implementations • 30 Sep 2022 • Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron Musco
We present a simple method that avoids both shortcomings: construct the line graph of the network, which includes a node for each interaction, and weigh the edges of this graph based on the difference in time between interactions.
no code implementations • 6 Sep 2022 • Jinhang Zuo, Songwen Hu, Tong Yu, Shuai Li, Handong Zhao, Carlee Joe-Wong
To achieve this, the recommender system conducts conversations with users, asking their preferences for different items or item categories.
1 code implementation • 31 Aug 2022 • Xutong Liu, Haoru Zhao, Tong Yu, Shuai Li, John C. S. Lui
Contextual multi-armed bandit (MAB) is an important sequential decision-making problem in recommendation systems.
1 code implementation • 21 Aug 2022 • Zhihui Xie, Tong Yu, Canzhe Zhao, Shuai Li
To enable users to provide comparative preferences during conversational interactions, we propose a novel comparison-based conversational recommender system.
1 code implementation • 26 Jul 2022 • Zhankui He, Handong Zhao, Tong Yu, Sungchul Kim, Fan Du, Julian McAuley
MCR, which uses a conversational paradigm to elicit user interests by asking user preferences on tags (e. g., categories or attributes) and handling user feedback across multiple rounds, is an emerging recommendation setting to acquire user feedback and narrow down the output space, but has not been explored in the context of bundle recommendation.
1 code implementation • 1 Jul 2022 • Sanat Ramesh, Vinkle Srivastav, Deepak Alapatt, Tong Yu, Aditya Murali, Luca Sestini, Chinedu Innocent Nwoye, Idris Hamoud, Saurav Sharma, Antoine Fleurentin, Georgios Exarchakis, Alexandros Karargyris, Nicolas Padoy
Correct transfer of these methods to surgery, as described and conducted in this work, leads to substantial performance gains over generic uses of SSL - up to 7. 4% on phase recognition and 20% on tool presence detection - as well as state-of-the-art semi-supervised phase recognition approaches by up to 14%.
Ranked #1 on Semantic Segmentation on Endoscapes
1 code implementation • 12 Jun 2022 • Ruslan Khalitov, Tong Yu, Lei Cheng, Zhirong Yang
Sequential data naturally have different lengths in many domains, with some very long sequences.
Ranked #4 on Long-range modeling on LRA
1 code implementation • CVPR 2022 • Tong Yu, Ruslan Khalitov, Lei Cheng, Zhirong Yang
The overall computing cost of the new building block is as low as $O(N \log N)$.
Ranked #18 on Long-range modeling on LRA
6 code implementations • 10 Apr 2022 • Chinedu Innocent Nwoye, Deepak Alapatt, Tong Yu, Armine Vardazaryan, Fangfang Xia, Zixuan Zhao, Tong Xia, Fucang Jia, Yuxuan Yang, Hao Wang, Derong Yu, Guoyan Zheng, Xiaotian Duan, Neil Getty, Ricardo Sanchez-Matilla, Maria Robu, Li Zhang, Huabin Chen, Jiacheng Wang, Liansheng Wang, Bokai Zhang, Beerend Gerats, Sista Raviteja, Rachana Sathish, Rong Tao, Satoshi Kondo, Winnie Pang, Hongliang Ren, Julian Ronald Abbing, Mohammad Hasan Sarhan, Sebastian Bodenstedt, Nithya Bhasker, Bruno Oliveira, Helena R. Torres, Li Ling, Finn Gaida, Tobias Czempiel, João L. Vilaça, Pedro Morais, Jaime Fonseca, Ruby Mae Egging, Inge Nicole Wijma, Chen Qian, GuiBin Bian, Zhen Li, Velmurugan Balasubramanian, Debdoot Sheet, Imanol Luengo, Yuanbo Zhu, Shuai Ding, Jakob-Anton Aschenbrenner, Nicolas Elini van der Kar, Mengya Xu, Mobarakol Islam, Lalithkumar Seenivasan, Alexander Jenke, Danail Stoyanov, Didier Mutter, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Nicolas Padoy
In this paper, we present the challenge setup and assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge.
Ranked #1 on Action Triplet Recognition on CholecT50 (Challenge) (using extra training data)
no code implementations • 8 Mar 2022 • Tong Yu, Pietro Mascagni, Juan Verde, Jacques Marescaux, Didier Mutter, Nicolas Padoy
Searching through large volumes of medical data to retrieve relevant information is a challenging yet crucial task for clinical care.
no code implementations • 14 Feb 2022 • Zhaoyang Qu, Xiaoyong Bo, Tong Yu, Yaowei Liu, Yunchang Dong, Zhongfeng Kan, Lei Wang, Yang Li
Taking account of the fact that the existing knowledge-driven detection process for FDIAs has been in a passive detection state for a long time and ignores the advantages of data-driven active capture of features, an active and passive hybrid detection method for power CPS FDIAs with improved adaptive Kalman filter (AKF) and convolutional neural networks (CNN) is proposed in this paper.
1 code implementation • 6 Jan 2022 • Lei Cheng, Ruslan Khalitov, Tong Yu, Zhirong Yang
Recurrent Neural Networks, Transformers, and Convolutional Neural Networks are three major techniques for learning from sequential data.
no code implementations • CVPR 2022 • Yufan Zhou, Ruiyi Zhang, Changyou Chen, Chunyuan Li, Chris Tensmeyer, Tong Yu, Jiuxiang Gu, Jinhui Xu, Tong Sun
One of the major challenges in training text-to-image generation models is the need of a large number of high-quality text-image pairs.
no code implementations • CVPR 2022 • Haoyu Ma, Handong Zhao, Zhe Lin, Ajinkya Kale, Zhangyang Wang, Tong Yu, Jiuxiang Gu, Sunav Choudhary, Xiaohui Xie
recommendation, and marketing services.
no code implementations • 13 Dec 2021 • Zhaoyang Qu, Yunchang Dong, Sylvère Mugemanyi, Tong Yu, Xiaoyong Bo, Huashun Li, Yang Li, François Xavier Rugema, Christophe Bananeza
DeGBBBA is an advanced variant of GBBBA in which a modified Gaussian distribution is introduced so as to allow the dynamic adaptation of exploitation and exploitation in the proposed algorithm.
2 code implementations • 27 Nov 2021 • Yufan Zhou, Ruiyi Zhang, Changyou Chen, Chunyuan Li, Chris Tensmeyer, Tong Yu, Jiuxiang Gu, Jinhui Xu, Tong Sun
One of the major challenges in training text-to-image generation models is the need of a large number of high-quality image-text pairs.
Ranked #2 on Text-to-Image Generation on Multi-Modal-CelebA-HQ
no code implementations • the 29th ACM International Conference on Multimedia 2021 • Junda Wu, Tong Yu, Shuai Li
Vision-language explanations in the systems can better guide users to provide feedback and thus improve the retrieval.
1 code implementation • 10 Oct 2021 • Shaohua Wu, Xudong Zhao, Tong Yu, Rongguo Zhang, Chong Shen, Hongli Liu, Feng Li, Hong Zhu, Jiangang Luo, Liang Xu, Xuanwei Zhang
With this method, Yuan 1. 0, the current largest singleton language model with 245B parameters, achieves excellent performance on thousands GPUs during training, and the state-of-the-art results on NLP tasks.
no code implementations • 30 Sep 2021 • Martin Wagner, Beat-Peter Müller-Stich, Anna Kisilenko, Duc Tran, Patrick Heger, Lars Mündermann, David M Lubotsky, Benjamin Müller, Tornike Davitashvili, Manuela Capek, Annika Reinke, Tong Yu, Armine Vardazaryan, Chinedu Innocent Nwoye, Nicolas Padoy, Xinyang Liu, Eung-Joo Lee, Constantin Disch, Hans Meine, Tong Xia, Fucang Jia, Satoshi Kondo, Wolfgang Reiter, Yueming Jin, Yonghao Long, Meirui Jiang, Qi Dou, Pheng Ann Heng, Isabell Twick, Kadir Kirtac, Enes Hosgor, Jon Lindström Bolmgren, Michael Stenzel, Björn von Siemens, Hannes G. Kenngott, Felix Nickel, Moritz von Frankenberg, Franziska Mathis-Ullrich, Lena Maier-Hein, Stefanie Speidel, Sebastian Bodenstedt
PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems.
Ranked #1 on Surgical phase recognition on HeiChole Benchmark
1 code implementation • 16 Sep 2021 • Ruslan Khalitov, Tong Yu, Lei Cheng, Zhirong Yang
The sparse factorization method is tested for a variety of synthetic and real-world square matrices.
Ranked #17 on Long-range modeling on LRA
8 code implementations • 7 Sep 2021 • Chinedu Innocent Nwoye, Tong Yu, Cristians Gonzalez, Barbara Seeliger, Pietro Mascagni, Didier Mutter, Jacques Marescaux, Nicolas Padoy
To achieve this task, we introduce our new model, the Rendezvous (RDV), which recognizes triplets directly from surgical videos by leveraging attention at two different levels.
Ranked #1 on Action Triplet Recognition on CholecT50
no code implementations • 24 Feb 2021 • Sanat Ramesh, Diego Dall'Alba, Cristians Gonzalez, Tong Yu, Pietro Mascagni, Didier Mutter, Jacques Marescaux, Paolo Fiorini, Nicolas Padoy
Conclusion: In this work, we present a multi-task multi-stage temporal convolutional network for surgical activity recognition, which shows improved results compared to single-task models on the Bypass40 gastric bypass dataset with multi-level annotations.
no code implementations • 30 Sep 2020 • Tong Yu, Nicolas Padoy
This paper tackles a new problem in computer vision: mid-stream video-to-video retrieval.
4 code implementations • 10 Jul 2020 • Chinedu Innocent Nwoye, Cristians Gonzalez, Tong Yu, Pietro Mascagni, Didier Mutter, Jacques Marescaux, Nicolas Padoy
Recognition of surgical activity is an essential component to develop context-aware decision support for the operating room.
Ranked #1 on Action Triplet Recognition on CholecT40
no code implementations • 9 Jul 2020 • Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel
We propose a novel framework for structured bandits, which we call an influence diagram bandit.
no code implementations • 4 May 2020 • Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen, Lawrence Carin
Text-based interactive recommendation provides richer user feedback and has demonstrated advantages over traditional interactive recommender systems.
1 code implementation • 12 Mar 2020 • Tong Yu, Hong Zhu
This study next reviews major services and toolkits for HPO, comparing their support for state-of-the-art searching algorithms, feasibility with major deep learning frameworks, and extensibility for new modules designed by users.
no code implementations • NeurIPS 2019 • Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen
Text-based interactive recommendation provides richer user preferences and has demonstrated advantages over traditional interactive recommender systems.
no code implementations • 7 Jun 2019 • Charles Chen, Ruiyi Zhang, Eunyee Koh, Sungchul Kim, Scott Cohen, Tong Yu, Ryan Rossi, Razvan Bunescu
In this work, we investigate the problem of figure captioning where the goal is to automatically generate a natural language description of the figure.
no code implementations • 7 Dec 2018 • Jianfeng Chi, Emmanuel Owusu, Xuwang Yin, Tong Yu, William Chan, Patrick Tague, Yuan Tian
We present a practical method for protecting data during the inference phase of deep learning based on bipartite topology threat modeling and an interactive adversarial deep network construction.
1 code implementation • 30 Nov 2018 • Tong Yu, Didier Mutter, Jacques Marescaux, Nicolas Padoy
Vision algorithms capable of interpreting scenes from a real-time video stream are necessary for computer-assisted surgery systems to achieve context-aware behavior.
no code implementations • 7 Oct 2018 • Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian Lane, Xiaobing Liu
To address these issues, we propose two attention models for human activity recognition: temporal attention and sensor attention.
no code implementations • 22 Jan 2018 • Ming Zeng, Tong Yu, Xiao Wang, Le T. Nguyen, Ole J. Mengshoel, Ian Lane
Labeled data used for training activity recognition classifiers are usually limited in terms of size and diversity.
no code implementations • 22 Nov 2017 • Bing Liu, Tong Yu, Ian Lane, Ole J. Mengshoel
Moreover, we report encouraging response selection performance of the proposed neural bandit model using the Recall@k metric for a small set of online training samples.
no code implementations • 21 Sep 2017 • Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
We study the problem of learning a latent variable model from a stream of data.