Machine Learning

Authors and titles for cs.LG in Mar 2023, skipping first 125

[126]  arXiv:2303.01557 [pdf, other]

Title: BenchDirect: A Directed Language Model for Compiler Benchmarks

Authors: Foivos Tsimpourlas, Pavlos Petoumenos, Min Xu, Chris Cummins, Kim Hazelwood, Ajitha Rajan, Hugh Leather

Comments: arXiv admin note: substantial text overlap with arXiv:2208.06555

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)

[127]  arXiv:2303.01560 [pdf, other]

Title: Active Learning and Bayesian Optimization: a Unified Perspective to Learn with a Goal

Authors: Francesco Di Fiore, Michela Nardelli, Laura Mainini

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[128]  arXiv:2303.01567 [pdf, other]

Title: Deep Neural Networks with Efficient Guaranteed Invariances

Authors: Matthias Rath, Alexandru Paul Condurache

Subjects: Machine Learning (cs.LG); Computer Vision and Pattern Recognition (cs.CV)

[129]  arXiv:2303.01569 [pdf, other]

Title: Chemically Transferable Generative Backmapping of Coarse-Grained Proteins

Authors: Soojung Yang, Rafael Gómez-Bombarelli

Comments: 18 pages

Subjects: Machine Learning (cs.LG); Biomolecules (q-bio.BM)

[130]  arXiv:2303.01590 [pdf, other]

Title: Technical report: Graph Neural Networks go Grammatical

Authors: Jason Piquenot, Aldo Moscatelli, Maxime Bérar, Pierre Héroux, Romain raveaux, Jean-Yves Ramel, Sébastien Adam

Comments: 24 pages, 11 figures

Subjects: Machine Learning (cs.LG); Computation and Language (cs.CL)

[131]  arXiv:2303.01610 [pdf, other]

Title: Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers

Authors: Tianlong Chen, Zhenyu Zhang, Ajay Jaiswal, Shiwei Liu, Zhangyang Wang

Comments: Codes and models are available in this https URL

Subjects: Machine Learning (cs.LG)

[132]  arXiv:2303.01621 [pdf, other]

Title: GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces

Authors: Josephine Lamp, Mark Derdzinski, Christopher Hannemann, Joost van der Linden, Lu Feng, Tianhao Wang, David Evans

Journal-ref: Advances in Neural Information Processing Systems 36 (2023)

Subjects: Machine Learning (cs.LG); Cryptography and Security (cs.CR)

[133]  arXiv:2303.01630 [pdf, other]

Title: Learning to Adapt to Online Streams with Distribution Shifts

Authors: Chenyan Wu, Yimu Pan, Yandong Li, James Z. Wang

Subjects: Machine Learning (cs.LG)

[134]  arXiv:2303.01668 [pdf, other]

Title: RePreM: Representation Pre-training with Masked Model for Reinforcement Learning

Authors: Yuanying Cai, Chuheng Zhang, Wei Shen, Xuyun Zhang, Wenjie Ruan, Longbo Huang

Comments: Accepted by AAAI-23

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)

[135]  arXiv:2303.01682 [pdf, other]

Title: Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks

Authors: Dat Phan-Trong, Hung Tran-The, Sunil Gupta

Subjects: Machine Learning (cs.LG)

[136]  arXiv:2303.01684 [pdf, other]

Title: BO-Muse: A human expert and AI teaming framework for accelerated experimental design

Authors: Sunil Gupta, Alistair Shilton, Arun Kumar A V, Shannon Ryan, Majid Abdolshah, Hung Le, Santu Rana, Julian Berk, Mahad Rashid, Svetha Venkatesh

Comments: 34 Pages, 7 Figures and 5 Tables

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)

[137]  arXiv:2303.01687 [pdf, other]

Title: Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation

Authors: Yilin Yang, Kamil Adamczewski, Danica J. Sutherland, Xiaoxiao Li, Mijung Park

Subjects: Machine Learning (cs.LG); Cryptography and Security (cs.CR); Computer Vision and Pattern Recognition (cs.CV)

[138]  arXiv:2303.01692 [pdf, other]

Title: Travel Demand Forecasting: A Fair AI Approach

Authors: Xiaojian Zhang, Qian Ke, Xilei Zhao

Comments: improved the methodology; updated new contents

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computers and Society (cs.CY)

[139]  arXiv:2303.01704 [pdf, other]

Title: Feature Importance Disparities for Data Bias Investigations

Authors: Peter W. Chang, Leor Fishman, Seth Neel

Comments: 10 pages, 7 figures. Appendix: 15 pages, 12 figures. Edits: Restructuring of paper with more emphasis on usefulness as a hypothesis generator for biased subgroups and features. Additional experiment tying our work to existing fairness work by observing fairness metrics of our discovered subgroups and measuring the FID of subgroups found using prior biased subgroup discovery methods

Subjects: Machine Learning (cs.LG); Computers and Society (cs.CY)

[140]  arXiv:2303.01713 [pdf, other]

Title: Convex Bounds on the Softmax Function with Applications to Robustness Verification

Authors: Dennis Wei, Haoze Wu, Min Wu, Pin-Yu Chen, Clark Barrett, Eitan Farchi

Comments: AISTATS 2023

Subjects: Machine Learning (cs.LG)

[141]  arXiv:2303.01724 [pdf, other]

Title: Node-Specific Space Selection via Localized Geometric Hyperbolicity in Graph Neural Networks

Authors: See Hian Lee, Feng Ji, Wee Peng Tay

Subjects: Machine Learning (cs.LG)

[142]  arXiv:2303.01728 [pdf, other]

Title: Guarded Policy Optimization with Imperfect Online Demonstrations

Authors: Zhenghai Xue, Zhenghao Peng, Quanyi Li, Zhihan Liu, Bolei Zhou

Comments: Accepted at ICLR 2023 (top 25%)

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Robotics (cs.RO)

[143]  arXiv:2303.01739 [pdf, other]

Title: Study of Distractors in Neural Models of Code

Authors: Md Rafiqul Islam Rabin, Aftab Hussain, Sahil Suneja, Mohammad Amin Alipour

Comments: The 1st International Workshop on Interpretability and Robustness in Neural Software Engineering, Co-located with ICSE (InteNSE'23)

Subjects: Machine Learning (cs.LG); Programming Languages (cs.PL); Software Engineering (cs.SE)

[144]  arXiv:2303.01748 [pdf, other]

Title: A Complete Recipe for Diffusion Generative Models

Authors: Kushagra Pandey, Stephan Mandt

Comments: Accepted in ICCV'23 (Oral Presentation)

Subjects: Machine Learning (cs.LG); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (stat.ML)

[145]  arXiv:2303.01767 [pdf, other]

Title: Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks

Authors: Ye Li, Song-Can Chen, Sheng-Jun Huang

Comments: 17 pages, published as a conference paper at AAAI23

Subjects: Machine Learning (cs.LG)

[146]  arXiv:2303.01768 [pdf, other]

Title: Toward Risk-based Optimistic Exploration for Cooperative Multi-Agent Reinforcement Learning

Authors: Jihwan Oh, Joonkee Kim, Minchan Jeong, Se-Young Yun

Comments: AAMAS2023 camera-ready version. First two authors contributed equally

Subjects: Machine Learning (cs.LG); Multiagent Systems (cs.MA)

[147]  arXiv:2303.01774 [pdf, other]

Title: Bayesian Optimization over High-Dimensional Combinatorial Spaces via Dictionary-based Embeddings

Authors: Aryan Deshwal, Sebastian Ament, Maximilian Balandat, Eytan Bakshy, Janardhan Rao Doppa, David Eriksson

Comments: Appearing in AISTATS 2023

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[148]  arXiv:2303.01775 [pdf, other]

Title: Continual Causal Inference with Incremental Observational Data

Authors: Zhixuan Chu, Ruopeng Li, Stephen Rathbun, Sheng Li

Comments: The 39th IEEE International Conference on Data Engineering (ICDE 2023). arXiv admin note: text overlap with arXiv:2301.01026

Subjects: Machine Learning (cs.LG); Machine Learning (stat.ML)

[149]  arXiv:2303.01778 [pdf, other]

Title: FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training

Authors: Zhenheng Tang, Xiaowen Chu, Ryan Yide Ran, Sunwoo Lee, Shaohuai Shi, Yonggang Zhang, Yuxin Wang, Alex Qiaozhong Liang, Salman Avestimehr, Chaoyang He

Subjects: Machine Learning (cs.LG); Distributed, Parallel, and Cluster Computing (cs.DC)

[150]  arXiv:2303.01792 [pdf, other]

Title: Graph-based Extreme Feature Selection for Multi-class Classification Tasks

Authors: Shir Friedman, Gonen Singer, Neta Rabin

Subjects: Machine Learning (cs.LG)