Machine Learning

Authors and titles for September 2021

[851] arXiv:2109.13825 [pdf, other]

Title: What to Prioritize? Natural Language Processing for the Development of a Modern Bug Tracking Solution in Hardware Development

Thi Thu Hang Do, Markus Dobler, Niklas Kühl

Comments: Hawaii International Conference on System Sciences 2022 (HICSS-55)

Subjects: Machine Learning (cs.LG)

[852] arXiv:2109.13828 [pdf, other]

Title: An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data

Xinze Li, Baixi Zou

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

[853] arXiv:2109.13851 [pdf, other]

Title: Reinforcement Learning for Quantitative Trading

Shuo Sun, Rundong Wang, Bo An

Subjects: Machine Learning (cs.LG); Computational Finance (q-fin.CP)

[854] arXiv:2109.13863 [pdf, other]

Title: A First-Occupancy Representation for Reinforcement Learning

Ted Moskovitz, Spencer R. Wilson, Maneesh Sahani

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

[855] arXiv:2109.13889 [pdf, other]

Title: A PAC-Bayesian Analysis of Distance-Based Classifiers: Why Nearest-Neighbour works!

Thore Graepel, Ralf Herbrich

Comments: This article was submitted to ICML 2000 and rejected; the references have not been updated since the submission in 2000

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

[856] arXiv:2109.13895 [pdf, other]

Title: Symbolic Regression by Exhaustive Search: Reducing the Search Space Using Syntactical Constraints and Efficient Semantic Structure Deduplication

Lukas Kammerer, Gabriel Kronberger, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller

Comments: Genetic and Evolutionary Computation

Journal-ref: In: Banzhaf W. et al (eds) Genetic Programming Theory and Practice XVII, pp 79-99 (2020)

Subjects: Machine Learning (cs.LG)

[857] arXiv:2109.13898 [pdf, other]

Title: Cluster Analysis of a Symbolic Regression Search Space

Gabriel Kronberger, Lukas Kammerer, Bogdan Burlacu, Stephan M. Winkler, Michael Kommenda, Michael Affenzeller

Comments: Genetic Programming Theory and Practice XVI. Genetic and Evolutionary Computation. Springer

Journal-ref: eIn: Banzhaf W. et al (eds) Genetic Programming Theory and Practice XVI. Genetic and Evolutionary Computation. Springer, Cham. pp 85-102 (2019)

Subjects: Machine Learning (cs.LG)

[858] arXiv:2109.13901 [pdf, other]

Title: Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning

Ziming Liu, Yunyue Chen, Yuanqi Du, Max Tegmark

Comments: 10 pages, 3 figures, 4 tables

Subjects: Machine Learning (cs.LG); Classical Physics (physics.class-ph); Computational Physics (physics.comp-ph); Data Analysis, Statistics and Probability (physics.data-an)

[859] arXiv:2109.13916 [pdf, other]

Title: Unsolved Problems in ML Safety

Dan Hendrycks, Nicholas Carlini, John Schulman, Jacob Steinhardt

Comments: Position Paper

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV)

[860] arXiv:2109.13963 [pdf, other]

Title: Smart at what cost? Characterising Mobile Deep Neural Networks in the wild

Mario Almeida, Stefanos Laskaridis, Abhinav Mehrotra, Lukasz Dudziak, Ilias Leontiadis, Nicholas D. Lane

Comments: Accepted at the ACM Internet Measurement Conference (IMC), 2021

Subjects: Machine Learning (cs.LG); Performance (cs.PF)

[861] arXiv:2109.13977 [pdf, other]

Title: Risk averse non-stationary multi-armed bandits

Leo Benac, Frédéric Godin

Subjects: Machine Learning (cs.LG)

[862] arXiv:2109.13983 [pdf, other]

Title: Guidelines for the Computational Testing of Machine Learning approaches to Vehicle Routing Problems

Luca Accorsi, Andrea Lodi, Daniele Vigo

Subjects: Machine Learning (cs.LG)

[863] arXiv:2109.13986 [pdf, other]

Title: Symbolic Brittleness in Sequence Models: on Systematic Generalization in Symbolic Mathematics

Sean Welleck, Peter West, Jize Cao, Yejin Choi

Comments: AAAI 2022

Subjects: Machine Learning (cs.LG)

[864] arXiv:2109.13995 [pdf, other]

Title: IGLU: Efficient GCN Training via Lazy Updates

S Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam

Comments: Published as Conference Paper at ICLR 2022, 36 Pages

Subjects: Machine Learning (cs.LG)

[865] arXiv:2109.14002 [pdf, other]

Title: slimTrain -- A Stochastic Approximation Method for Training Separable Deep Neural Networks

Elizabeth Newman, Julianne Chung, Matthias Chung, Lars Ruthotto

Comments: 26 pages, 10 figures, 1 table

Subjects: Machine Learning (cs.LG); Numerical Analysis (math.NA); Machine Learning (stat.ML)

[866] arXiv:2109.14035 [pdf, other]

Title: Formalizing the Generalization-Forgetting Trade-off in Continual Learning

Krishnan Raghavan, Prasanna Balaprakash

Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Dynamical Systems (math.DS); Optimization and Control (math.OC)

[867] arXiv:2109.14041 [pdf, other]

Title: Local Repair of Neural Networks Using Optimization

Keyvan Majd, Siyu Zhou, Heni Ben Amor, Georgios Fainekos, Sriram Sankaranarayanan

Subjects: Machine Learning (cs.LG); Systems and Control (eess.SY)

[868] arXiv:2109.14099 [pdf, other]

Title: An Explainable-AI approach for Diagnosis of COVID-19 using MALDI-ToF Mass Spectrometry

Venkata Devesh Reddy Seethi, Zane LaCasse, Prajkta Chivte, Joshua Bland, Shrihari S. Kadkol, Elizabeth R. Gaillard, Pratool Bharti, Hamed Alhoori

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

[869] arXiv:2109.14117 [pdf, other]

Title: Neural Network Ensembles: Theory, Training, and the Importance of Explicit Diversity

Wenjing Li, Randy C. Paffenroth, David Berthiaume

Subjects: Machine Learning (cs.LG)

[870] arXiv:2109.14119 [pdf, other]

Title: Stochastic Training is Not Necessary for Generalization

Jonas Geiping, Micah Goldblum, Phillip E. Pope, Michael Moeller, Tom Goldstein

Comments: 25 pages, 6 figures. Code published at this http URL. Decompressed version of paper published at ICLR 2022

Subjects: Machine Learning (cs.LG); Optimization and Control (math.OC)

[871] arXiv:2109.14120 [pdf, other]

Title: Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awareness

Zhenyi Wang, Tiehang Duan, Le Fang, Qiuling Suo, Mingchen Gao

Comments: ICCV 2021

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

[872] arXiv:2109.14124 [pdf, other]

Title: Vitruvion: A Generative Model of Parametric CAD Sketches

Ari Seff, Wenda Zhou, Nick Richardson, Ryan P. Adams

Comments: ICLR camera ready

Journal-ref: ICLR 2022

Subjects: Machine Learning (cs.LG)

[873] arXiv:2109.14142 [pdf, other]

Title: On the Provable Generalization of Recurrent Neural Networks

Lifu Wang, Bo Shen, Bo Hu, Xing Cao

Comments: Accepted to Neurips 2021

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

[874] arXiv:2109.14147 [pdf, other]

Title: Temporal Clustering with External Memory Network for Disease Progression Modeling

Zicong Zhang, Changchang Yin, Ping Zhang

Subjects: Machine Learning (cs.LG)

[875] arXiv:2109.14158 [pdf, other]

Title: Second-Order Neural ODE Optimizer

Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou

Comments: Accepted to Advances in Neural Information Processing Systems (NeurIPS) 2021 as Spotlight

Subjects: Machine Learning (cs.LG); Systems and Control (eess.SY); Optimization and Control (math.OC)

[876] arXiv:2109.14159 [pdf, other]

Title: Adaptive Multi-layer Contrastive Graph Neural Networks

Shuhao Shi, Pengfei Xie, Xu Luo, Kai Qiao, Linyuan Wang, Jian Chen, Bin Yan

Comments: 16 pages,7 figures

Journal-ref: Neural Processing Letters 55 (2021): 4757 - 4776

Subjects: Machine Learning (cs.LG)

[877] arXiv:2109.14162 [pdf, other]

Title: Can multi-label classification networks know what they don't know?

Haoran Wang, Weitang Liu, Alex Bocchieri, Yixuan Li

Comments: Paper published at NeurIPS 2021

Subjects: Machine Learning (cs.LG)

[878] arXiv:2109.14180 [pdf, other]

Title: Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy

Kunpeng Liu, Pengfei Wang, Dongjie Wang, Wan Du, Dapeng Oliver Wu, Yanjie Fu

Comments: ICDM 2021

Subjects: Machine Learning (cs.LG)

[879] arXiv:2109.14188 [pdf, other]

Title: Information-Bottleneck-Based Behavior Representation Learning for Multi-agent Reinforcement learning

Yue Jin, Shuangqing Wei, Jian Yuan, Xudong Zhang

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

[880] arXiv:2109.14198 [pdf, other]

Title: Breaking the curse of dimensionality with Isolation Kernel

Kai Ming Ting, Takashi Washio, Ye Zhu, Yang Xu

Subjects: Machine Learning (cs.LG)

[881] arXiv:2109.14213 [pdf, other]

Title: On the One-sided Convergence of Adam-type Algorithms in Non-convex Non-concave Min-max Optimization

Zehao Dou, Yuanzhi Li

Comments: 44 pages

Subjects: Machine Learning (cs.LG); Optimization and Control (math.OC); Machine Learning (stat.ML)

[882] arXiv:2109.14218 [pdf, other]

Title: Equivariant Neural Network for Factor Graphs

Fan-Yun Sun, Jonathan Kuck, Hao Tang, Stefano Ermon

Subjects: Machine Learning (cs.LG)

[883] arXiv:2109.14235 [pdf, other]

Title: Error rate control for classification rules in multiclass mixture models

Tristan Mary-Huard (GQE-Le Moulon, MIA-Paris), Vittorio Perduca (MAP5 - UMR 8145), Gilles Blanchard (LMO, DATASHAPE), Martin-Magniette Marie-Laure (IPS2 (UMR\_9213 / UMR\_1403), MIA-Paris)

Subjects: Machine Learning (cs.LG); Statistics Theory (math.ST); Machine Learning (stat.ML)

[884] arXiv:2109.14236 [pdf, other]

Title: LightSecAgg: a Lightweight and Versatile Design for Secure Aggregation in Federated Learning

Jinhyun So, Chaoyang He, Chien-Sheng Yang, Songze Li, Qian Yu, Ramy E. Ali, Basak Guler, Salman Avestimehr

Comments: This paper is accepted to the 5th MLSys Conference, Santa Clara, CA, USA, 2022

Subjects: Machine Learning (cs.LG); Cryptography and Security (cs.CR); Distributed, Parallel, and Cluster Computing (cs.DC); Information Theory (cs.IT); Machine Learning (stat.ML)

[885] arXiv:2109.14248 [pdf, other]

Title: EBSD Grain Knowledge Graph Representation Learning for Material Structure-Property Prediction

Chao Shu, Zhuoran Xin, Cheng Xie

Subjects: Machine Learning (cs.LG)

[886] arXiv:2109.14251 [pdf, other]

Title: Road Network Guided Fine-Grained Urban Traffic Flow Inference

Lingbo Liu, Mengmeng Liu, Guanbin Li, Ziyi Wu, Junfan Lin, Liang Lin

Comments: This work has been accepted to TNNLS

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

[887] arXiv:2109.14268 [pdf, other]

Title: Formulation and validation of a car-following model based on deep reinforcement learning

Fabian Hart, Ostap Okhrin, Martin Treiber

Subjects: Machine Learning (cs.LG); Robotics (cs.RO); Signal Processing (eess.SP)

[888] arXiv:2109.14271 [pdf, other]

Title: (Machine) Learning to Improve the Empirical Performance of Discrete Algorithms

Imran Adham, Jesus De Loera, Zhenyang Zhang

Subjects: Machine Learning (cs.LG); Combinatorics (math.CO); Optimization and Control (math.OC)

[889] arXiv:2109.14274 [pdf, other]

Title: Designing Counterfactual Generators using Deep Model Inversion

Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Deepta Rajan, Jason Liang, Akshay Chaudhari, Andreas Spanias

Comments: Neurips 2021

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

[890] arXiv:2109.14276 [pdf, other]

Title: Sequential Deep Learning Architectures for Anomaly Detection in Virtual Network Function Chains

Chungjun Lee, Jibum Hong, DongNyeong Heo, Heeyoul Choi

Subjects: Machine Learning (cs.LG); Networking and Internet Architecture (cs.NI)

[891] arXiv:2109.14285 [pdf, other]

Title: Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration

Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang

Comments: Accepted to NeurIPS 2021

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

[892] arXiv:2109.14288 [pdf, other]

Title: Self-Supervised Learning for 3D Medical Image Analysis using 3D SimCLR and Monte Carlo Dropout

Yamen Ali, Aiham Taleb, Marina M. -C. Höhne, Christoph Lippert

Subjects: Machine Learning (cs.LG); Computer Vision and Pattern Recognition (cs.CV); Image and Video Processing (eess.IV)

[893] arXiv:2109.14311 [pdf, other]

Title: Learning Dynamics Models for Model Predictive Agents

Michael Lutter, Leonard Hasenclever, Arunkumar Byravan, Gabriel Dulac-Arnold, Piotr Trochim, Nicolas Heess, Josh Merel, Yuval Tassa

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

[894] arXiv:2109.14333 [pdf, other]

Title: Distribution Knowledge Embedding for Graph Pooling

Kaixuan Chen, Jie Song, Shunyu Liu, Na Yu, Zunlei Feng, Gengshi Han, Mingli Song

Comments: 10 pages, 5 figures, 5 tables

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

[895] arXiv:2109.14337 [pdf, other]

Title: Deep Reinforcement Q-Learning for Intelligent Traffic Signal Control with Partial Detection

Romain Ducrocq, Nadir Farhi

Comments: 9 pages

Subjects: Machine Learning (cs.LG); Systems and Control (eess.SY); Optimization and Control (math.OC)

[896] arXiv:2109.14375 [pdf, other]

Title: Dynamic Regret Analysis for Online Meta-Learning

Parvin Nazari, Esmaile Khorram

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

[897] arXiv:2109.14376 [pdf, other]

Title: Fairness-Driven Private Collaborative Machine Learning

Dana Pessach, Tamir Tassa, Erez Shmueli

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

[898] arXiv:2109.14412 [pdf, html, other]

Title: Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification

James A. Grant, David S. Leslie

Comments: Update to Theorem 1 and experimental work

Subjects: Machine Learning (cs.LG)

[899] arXiv:2109.14419 [pdf, other]

Title: On the Estimation Bias in Double Q-Learning

Zhizhou Ren, Guangxiang Zhu, Hao Hu, Beining Han, Jianglun Chen, Chongjie Zhang

Comments: Thirty-Fifth Conference on Neural Information Processing Systems (NeurIPS 2021)

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

[900] arXiv:2109.14422 [pdf, other]

Title: Multi-class Probabilistic Bounds for Self-learning

Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

Comments: 46 pages, 4 figures

Subjects: Machine Learning (cs.LG)