Elamur Research⌕
☰
home / venues / ICML / 2021 / papers / page 2

ICML 2021: all accepted papers

196 papers · page 2 of 2 · the most cited first · ← ICML 2021

1 2

  1. Refining Ice Layer Tracking through Wavelet combined Neural Networks ↗Debvrat Varshney, Masoud Yari, Tashnim Chowdhury et al.2 citations
  2. Reinforcement Learning for Cost-Aware Markov Decision Processes ↗Wesley A. Suttle, Kaiqing Zhang, Zhuoran Yang et al.2 citations
  3. SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis ↗Yuhan Liu, Shiliang Sun2 citations
  4. Solar PV Maps for Estimation and Forecasting of Distributed Solar Generation ↗Julian de Hoog, Maneesha Perera, Kasun Bandara et al.2 citations
  5. Strategically-timed State-Observation Attacks on Deep Reinforcement Learning Agents ↗You Qiaoben, Xinning Zhou, Chengyang Ying et al.2 citations
  6. Systematic Analysis of Cluster Similarity Indices: How to Validate Validation Measures ↗Martijn Gösgens, Aleksei Tikhonov, Liudmila Prokhorenkova2 citations
  7. A Novel Method to Solve Neural Knapsack Problems ↗Duanshun Li, Dong‐Eun Lee, Ali Seyedmazloom et al.1 citation
  8. A Proxy Variable View of Shared Confounding ↗Zhaoran Wang, David M. Blei1 citation
  9. A Receptor Skeleton for Capsule Neural Networks ↗Jintai Chen, Hongyun Yu, Chengde Qian et al.1 citation
  10. Adaptive Sampling for Best Policy Identification in Markov Decision Processes ↗Aymen Al Marjani, Alexandre Proutière1 citation
  11. Adversarial Sample Detection via Channel Pruning ↗Zuohui Chen, RenXuan Wang, Yao Lu et al.1 citation
  12. Agent Forecasting at Flexible Horizons using ODE Flows ↗Alexander Radovic, Jiawei He, Janahan Ramanan et al.1 citation
  13. Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication ↗Sangwoo Hong, Heecheol Yang, YoungSeok Yoon et al.1 citation
  14. Consistent Nonparametric Methods for Network Assisted Covariate Estimation ↗Xueyu Mao, Deepayan Chakrabarti, Purnamrita Sarkar1 citation
  15. Context-Aware Online Collective Inference for Templated Graphical Models ↗Charles Dickens, Connor Pryor, Eriq Augustine et al.1 citation
  16. Exploration-Driven Representation Learning in Reinforcement Learning ↗Akram Erraqabi, Mingde Zhao, Marlos C. Machado et al.1 citation
  17. Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation ↗Sungwoo Park, Dong Shu, Junseok Kwon1 citation
  18. Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees ↗Anand Rajagopalan, Fabio Vitale, Danny Vainstein et al.1 citation
  19. Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold ↗Wenkai Xu, Takeru Matsuda1 citation
  20. Marginalized Stochastic Natural Gradients for Black-Box Variational Inference ↗Geng Ji, Debora Sujono, Erik B. Sudderth1 citation
  21. Nonparametric Decomposition of Sparse Tensors ↗Conor A. Tillinghast, Shandian Zhe1 citation
  22. On Estimation in Latent Variable Models ↗Guanhua Fang, Ping Li1 citation
  23. On Monotonic Linear Interpolation of Neural Network Parameters ↗James Lucas, Juhan Bae, Michael Zhang et al.1 citation
  24. On the Effectiveness of Poisoning against Unsupervised Domain Adaptation ↗Akshay Mehra, Bhavya Kailkhura, Pin‐Yu Chen et al.1 citation
  25. Preserving the integrity of the Canadian northern ecosystems through insights provided by reinforcement learning-based Arctic fox movement models ↗Catherine Villeneuve, Frédéric Dulude‐de Broin, Pierre Legagneux et al.1 citation
  26. Reinforcement Learning Under Moral Uncertainty ↗Adrien Ecoffet, Joel Lehman1 citation
  27. Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing ↗Yuan Qing Deng, Sebastien M. Lahaie, Vahab Mirrokni et al.1 citation
  28. Robust Asymmetric Learning in POMDPs ↗Andrew Warrington, Jonathan Wilder Lavington, Adam Ścibior et al.1 citation
  29. Seasonal Sea Ice Presence Forecasting of Hudson Bay using Seq2Seq Learning ↗Nazanin Asadi, K. Andrea Scott, Philippe Lamontagne1 citation
  30. Trees with Attention for Set Prediction Tasks ↗Roy Hirsch, Ran Gilad-Bachrach1 citation
  31. Unsupervised Part Representation by Flow Capsules ↗Sara Sabour, Andrea Tagliasacchi, Soroosh Yazdani et al.1 citation
  32. Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data ↗Sungwoo Park, Junseok Kwon1 citation
  33. A Scalable Deterministic Global Optimization Algorithm for Clustering Problems ↗Kaixun Hua, Mingfei Shi, Yankai Cao
  34. A Unified Bayesian Framework for Discriminative and Generative Continual Learning ↗Abhishek Kumar, Sunabha Chatterjee, Piyush Rai
  35. A case study of a school with Slovene as the language of instruction in Vermegliano/Romjan (Italy) : teaching Slovene as L1 in classes with a prevailing Italian-speaking student population ↗Maja Melinc Mlekuž, Federico Tenca Montini
  36. A multi-task learning approach to enhance sustainable biomolecule production in engineered microorganisms ↗Erin H. Wilson, Mary E. Lidstrom, David A. C. Beck
  37. Additive Error Guarantees for Weighted Low Rank Approximation ↗Aditya Bhaskara, Aravinda Kanchana Ruwanpathirana, Pruthuvi Maheshakya Wijewardena
  38. An Integer Linear Programming Framework for Mining Constraints from Data ↗Tao Meng, Kai-Wei Chang
  39. Approximating a Distribution Using Weight Queries ↗Nadav Barak, Sivan Sabato A
  40. Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-Norm Least Squares Estimator ↗Zeng Li, Chuanlong Xie, Qinwen Wang
  41. BasisDeVAE: Interpretable Simultaneous Dimensionality Reduction and Feature-Level Clustering with Derivative-Based Variational Autoencoders ↗Dominic Danks, Christopher Yau
  42. CURI: A Benchmark for Productive Concept Learning Under Uncertainty ↗Shanmukha Ramakrishna Vedantam, Arthur D. Szlam, Maximilian Nickel et al.
  43. Challenges for BBVI with Normalizing Flows ↗Akash Kumar Dhaka, Alejandro Catalina, Manushi K. V. Welandawe et al.
  44. Conformal Embedding Flows: Tractable Density Estimation on Learned Manifolds ↗Brendan Leigh Ross, Jesse C. Cresswell
  45. Crystallization Learning with the Delaunay Triangulation ↗Jiaqi Gu, Guosheng Yin
  46. Deep Signature Statistics for Likelihood-free Time-series Models ↗Joel Dyer, Patrick W Cannon, Sebastian M. Schmon
  47. DeepPolicyTracker: Tracking Changes In Environmental Policy In The Brazilian Federal Official Gazette With Deep Learning ↗Flávio Nakasato Cação, Anna Helena Reali Costa, Natalie Unterstell et al.
  48. Defending Adversaries Using Unsupervised Feature Clustering VAE ↗Cheng Zhang, Pan Gao
  49. Discovering Weight Initializers with Meta Learning ↗Dmitry Baranchuk, Artem Babenko
  50. Disentangled Predictive Representation for Meta-Reinforcement Learning ↗Sephora Madjiheurem, Laura Toni
  51. Dueling Convex Optimization ↗Aadirupa Saha, Tomer Koren, Yishay Mansour
  52. Enhancing Laboratory-scale Flow Imaging of Fractured Geological Media with Deep Learning Super Resolution ↗Manju Pharkavi Murugesu, Timothy I. Anderson, Niccolò Dal Santo et al.
  53. Examining the nexus of environmental policy, climate physics, and maritime shipping with deep learning models and space-borne data ↗Tianle Yuan, Hua Song, Chenxi Wang et al.
  54. Factor-analytic inverse regression for high-dimension, small-sample dimensionality reduction ↗Aditi Jha, Michael J. Morais, Jonathan W. Pillow
  55. Finding k in Latent k- polytope ↗Chiranjib Bhattacharyya, Ravindran Kannan, Amit Kumar
  56. Forecasting Sea Ice Concentrations using Attention-based Ensemble LSTM ↗Sahara Ali, Yiyi Huang, Xin Huang et al.
  57. Forecasting emissions through Kaya identity using Neural ODEs ↗Pierre Browne
  58. Generalizing Adversarial Training to Composite Semantic Perturbations ↗Yun-Yun Tsai, Lei Hsiung, Pin‐Yu Chen et al.
  59. Guided A* Search for Scheduling Power Generation Under Uncertainty ↗Patrick de Mars, Aïdan O'Sullivan
  60. Householder Sketch for Accurate and Accelerated Least-Mean-Squares Solvers ↗Jyotikrishna Dass, Rabi Mahapatra
  61. Improving Continuous Normalizing Flows using a Multi-Resolution Framework ↗Vikram Voleti, Chris Finlay, Adam M. Oberman et al.
  62. Improving Image-Based Characterization of Porous Media with Deep Generative Models ↗Timothy I. Anderson, Kelly M. Guan, Bolivia Vega et al.
  63. Is It Time to Redefine the Classification Task for Deep Learning Systems ↗Keji Han, Yun Li, Songcan Chen
  64. Learning Optimal Auctions with Correlated Valuations from Samples ↗Yang Chunxue, Xiaohui Bei
  65. Learning from Nested Data with Ornstein Auto-Encoders ↗Youngwon Choi, Sungdong Lee, Joong‐Ho Won
  66. Learning to Represent State with Perceptual Schemata ↗Wilka Carvalho, Murray Shanahan
  67. Leveraging Machine Learning for Equitable Transition of Energy Systems ↗Enea Dodi, Anupama Sitaraman, Mohammad Hajiesmaili et al.
  68. Long-term Burned Area Reconstruction through Deep Learning ↗Seppe Lampe, Bertrand Le Saux, Inne Vanderkelen et al.
  69. MASAI: Multi-agent Summative Assessment Improvement for Unsupervised Environment Design ↗Yiping Wang, Michael Brandon Haworth
  70. Maximizing the robust margin provably overfits on noiseless data ↗Konstantin Donhauser, Alexandru Ţifrea, Michael Aerni et al.
  71. Modeling Bird Migration by Disaggregating Population Level Observations ↗Miguel Fuentes, Benjamin Mark Van Doren, Daniel R. Sheldon
  72. Multiple steps to the precipice: Risk aversion and worry in sequential decision-making ↗Peter Dayan, Chris Gagne
  73. Narrow Margins: Classification, Margins and Fat Tails ↗Francois Buet-Golfouse
  74. NeuralNERE: Neural Named Entity Relationship Extraction for End-to-End Climate Change Knowledge Graph Construction ↗Prakamya Mishra, Rohan Mittal
  75. Neuro-algorithmic Policies Enable Fast Combinatorial Generalization ↗Marin Vlastelica, Michal Rolínek, Georg Martius
  76. Non-Robust Feature Mapping in Deep Reinforcement Learning ↗Ezgi Korkmaz
  77. Nonmyopic Multifidelity Acitve Search ↗Quan Nguyen, Arghavan Modiri, Roman Garnett
  78. Objective Bound Conditional Gaussian Process for Bayesian Optimization ↗Taewon Jeong, Heeyoung Kim
  79. Online Selection Problems against Constrained Adversary ↗Zhihao Jiang, Pinyan Lu, Zhihao Gavin Tang et al.
  80. Policy Caches with Successor Features ↗Mark William Nemecek, Ronald Parr
  81. Ranking Architectures by Feature Extraction Capabilities ↗Debadeepta Dey, Shital Shah, Sébastien Bubeck
  82. Reconstruction of Long-Term Historical Electricity Demand Data ↗Reshmi Ghosh, Michael Craig, H. Scott Matthews et al.
  83. Revealing the impact of global warming on climate modes using transparent machine learning and a suite of climate models ↗Maike Sonnewald, Redouane Lguensat, Aparna Radhakrishnan et al.
  84. Robust Recovery of Adversarial Examples ↗Tejas Bana, Jatan Loya, Siddhant Ravindra Kulkarni
  85. Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models ↗José Lezama, Wei Chen, Qiang Qiu
  86. SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies ↗Jim Fan, Guanzhi Wang, De-An Huang et al.
  87. Self-Supervised Learning on Multispectral Satellite Data for Near-Term Solar Forecasting ↗Akansha Singh Bansal, Trapit Bansal, David Irwin
  88. SparseDice: Imitation Learning for Temporally Sparse Data via Regularization ↗Alberto Rivas, Aleksandra Faust, İzzeddin Gür et al.
  89. Spectral vertex sparsifiers and pair-wise spanners over distributed graphs ↗Chunjiang Zhu, Qinqing Liu, Jinbo Bi
  90. Tangent Space Least Adaptive Clustering ↗James Buenfil, Samson Koelle, Marina Meilă
  91. Tilting the playing field: Dynamical loss functions for machine learning ↗Miguel Ruiz Garcia, Ge Zhang, Samuel S. Schoenholz et al.
  92. Time-series Forecasting of Ionospheric Space Weather using Ensemble Machine Learning ↗Randa Natraš, Mischa Schmidt
  93. Uncovering Universal Features: How Adversarial Training Improves Adversarial Transferability ↗Jacob M. Springer, Melanie Mitchell, Garrett T. Kenyon
  94. Whispering to DNN: A Speech Steganographic Scheme Based on Hidden Adversarial Examples for Speech Recognition Models ↗Haozhe Chen, Weiming Zhang, Kejiang Chen et al.
  95. Why be adversarial? Let's cooperate!: Cooperative Dataset Alignment via JSD Upper Bound ↗Wonwoong Cho, Ziyu Gong, David I. Inouye
  96. α-VAEs : Optimising variational inference by learning data-dependent divergence skew ↗J. Deasy, Tom Andrew McIver, Nikola Simidjievski et al.

1 2

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/2021/papers/page/2/