Overview
The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning. ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.
Amazon team
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Area chair
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Area chair
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Cédric ArchambeauArea chair
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Cho-Jui HsiehArea chair
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Area chair
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Area chair
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Senior area chair
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Area chair
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Senior area chair
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Area chair
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Area chair
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Area chair
Accepted publications
Workshops
ICLR 2023 Workshop on Trustworthy Machine Learning for Healthcare
May 3
ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation Models
May 4
ICLR 2023 Workshop on Successful Domain Generalization
May 4
In this workshop, we aim to work towards answering a single question: what do we need for successful domain generalization? We conjecture that additional information of some form is required for a general purpose learning methods to be successful in the DG setting. The purpose of this workshop is to identify possible sources of such information, and demonstrate how these extra sources of data can be leveraged to construct models that are robust to distribution shift.
Amazon Organizer: Aniket Deshmukh
Website: https://domaingen.github.io/
Amazon Organizer: Aniket Deshmukh
Website: https://domaingen.github.io/
ICLR 2023 Workshop on Deep Learning for Code (DL4C)
May 5
The second DL4C workshop will provide a vibrant virtual platform for researchers to share their work on deep learning for code, emphasizing recent advances and challenges, for example: HCI for Code, Evaluation for Code, Inference for Code, Responsible AI for Code, and Open Sourcing efforts in deep learning for code.
Amazon organizer: Zijian Wang
Amazon program committee: Ming Tan, Mingyue Shang, Qing Sun, Robert Giaquinto, Siddhartha Jain, Yang Li
Website: https://dl4c.github.io
Amazon organizer: Zijian Wang
Amazon program committee: Ming Tan, Mingyue Shang, Qing Sun, Robert Giaquinto, Siddhartha Jain, Yang Li
Website: https://dl4c.github.io
ICLR 2023 Workshop on Pitfalls of Limited Data and Computation for Trustworthy ML
May 5
ICLR 2023 Workshop on Practical Machine Learning for Developing Countries
May 5
ICLR 2023 Tiny Paper
May 5
Related content
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May 02, 2023Two recent trends in the theory of deep learning are examinations of the double-descent phenomenon and more-realistic approaches to neural kernel methods.
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May 02, 2023ICLR workshop sponsored by Amazon CodeWhisperer features Amazon papers on a novel contrastive-learning framework for causal language models and a way to gauge the robustness of code generation models.
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May 03, 2021Workshop at ICLR 2021 unites communities investigating synthetic data generation to improve machine learning and protect privacy.