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The Conference on Neural Information Processing Systems (NeurIPS) takes place this week, and the Amazon papers accepted there touch on a wide range of topics, from experimental design and human-robot interaction to recommender systems and real-time statistical estimation. Amid that diversity, a few topics come in for particular attention: optimization, privacy, tabular data, time series forecasting, vision-language models — and particularly reinforcement learning.
Code generation
Large language models of code fail at completing code with potential bugs
Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
Complex query answering
Complex query answering on eventuality knowledge graph with implicit logical constraints
Jiaxin Bai, Xin Liu, Weiqi Wang, Chen Luo, Yangqiu Song
Experimental design
Experimental designs for heteroskedastic variance
Justin Weltz, Tanner Fiez, Eric Laber, Alexander Volfovsky, Blake Mason, Houssam Nassif, Lalit Jain
Federated learning
Federated multi-objective learning
Haibo Yang, Zhuqing Liu, Jia Liu, Chaosheng Dong, Michinari Momma
Human-robot interaction
Alexa Arena: A user-centric interactive platform for embodied AI
Qiaozi (QZ) Gao, Govind Thattai, Suhaila Shakiah, Xiaofeng Gao, Shreyas Pansare, Vasu Sharma, Gaurav Sukhatme, Hangjie Shi, Bofei Yang, Desheng Zhang, Lucy Hu, Karthika Arumugam, Shui Hu, Matthew Wen, Dinakar Guthy, Cadence Chung, Rohan Khanna, Osman Ipek, Leslie Ball, Kate Bland, Heather Rocker, Michael Johnston, Reza Ghanadan, Dilek Hakkani-Tür, Prem Natarajan
Optimization
Bounce: Reliable high-dimensional Bayesian optimization for combinatorial and mixed spaces
Leonard Papenmeier, Luigi Nardi, Matthias Poloczek
Debiasing conditional stochastic optimization
Lie He, Shiva Kasiviswanathan
Distributionally robust Bayesian optimization with ϕ-divergences
Hisham Husain, Vu Nguyen, Anton van den Hengel
Ordinal classification
Conformal prediction sets for ordinal classification
Prasenjit Dey, Srujana Merugu, Sivaramakrishnan (Siva) Kaveri
Privacy
Creating a public repository for joining private data
James Cook, Milind Shyani, Nina Mishra
Scalable membership inference attacks via quantile regression
Martin Bertran Lopez, Shuai Tang, Michael Kearns, Jamie Morgenstern, Aaron Roth, Zhiwei Steven Wu
Real-time statistical estimation
Online robust non-stationary estimation
Abishek Sankararaman, Balakrishnan (Murali) Narayanaswamy
Recommender systems
Enhancing user intent capture in session-based recommendation with attribute patterns
Xin Liu, Zheng Li, Yifan Gao, Jingfeng Yang, Tianyu Cao, Zhengyang Wang, Bing Yin, Yangqiu Song
Reinforcement learning
Budgeting counterfactual for offline RL
Yao Liu, Pratik Chaudhari, Rasool Fakoor
Finite-time logarithmic Bayes regret upper bounds
Alexia Atsidakou, Branislav Kveton, Sumeet Katariya, Constantine Caramanis, Sujay Sanghavi
Resetting the optimizer in deep RL: An empirical study
Kavosh Asadi, Rasool Fakoor, Shoham Sabach
TD convergence: An optimization perspective
Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor
Transfer learning, reinforcement learning for adaptive control optimization under distribution shift
Pankaj Rajak, Wojciech Kowalinski, Fei Wang
Responsible AI
Improving fairness for spoken language understanding in atypical speech with text-to-speech
Helin Wang, Venkatesh Ravichandran, Milind Rao, Becky Lammers, Myra Sydnor, Nicholas Maragakis, Ankur A. Butala, Jayne Zhang, Victoria Chovaz, Laureano Moro-Velazquez
Tabular data
An inductive bias for tabular deep learning
Ege Beyazit, Jonathan Kozaczuk, Bo Li, Vanessa Wallace, Bilal Fadlallah
HYTREL: Hypergraph-enhanced tabular data representation learning
Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
Time series forecasting
Predict, refine, synthesize: Self-guiding diffusion models for probabilistic time series forecasting
Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang (Bernie) Wang
PreDiff: Precipitation nowcasting with latent diffusion models
Zhihan Gao, Xingjian Shi, Boran Han, Hao Wang, Xiaoyong Jin, Danielle Maddix Robinson, Yi Zhu, Mu Li, Yuyang (Bernie) Wang
Vision-language models
Prompt pre-training with twenty-thousand classes for open-vocabulary visual recognition
Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alex Smola, Xu Su
Your representations are in the network: Composable and parallel adaptation for large scale models
Yonatan Dukler, Alessandro Achille, Hao Yang, Ben Bowman, Varsha Vivek, Luca Zancato, Avinash Ravichandran, Charless Fowlkes, Ashwin Swaminathan, Stefano Soatto
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