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machine learning Research

Carnegie Mellon University at ICML 2020

July 13, 2020

Carnegie Mellon University is proud to present 44 papers at the 37th International Conference on Machine Learning (ICML 2020), which will be held virtually this week. CMU is also involved in organizing 5 workshops at the conference, and our faculty…

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computer vision machine learning Research

CATER: A diagnostic dataset for Compositional Actions and Temporal Reasoning

July 3, 2020

Introducing CATER: A diagnostic dataset for video understanding that, by design, requires temporal reasoning to be solved. While deep features have revolutionized static image analysis, deep video descriptors have struggled to outperform classic hand-crafted descriptors. Though recent works have shown…

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deep learning machine learning reinforcement learning Research

Learning to Explore using Active Neural SLAM

June 19, 2020

Active Neural SLAM is a modular navigation system that learns to explore unseen indoor environments. Advances in machine learning, computer vision and robotics have opened up avenues of building intelligent robots which can navigate in the physical world and perform…

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machine learning natural language processing Research

Differentiable Reasoning over Text

May 15, 2020

We all rely on search engines to navigate the massive amount of online information published every day. Modern search engines not only retrieve a list of pages relevant to a query but often try to directly answer our questions by…

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machine learning reinforcement learning Research

Unsupervised Meta-Learning: Learning to Learn without Supervision

May 1, 2020

The history of machine learning has largely been a story of increasing abstraction. In the dawn of ML, researchers spent considerable effort engineering features. As deep learning gained popularity, researchers then shifted towards tuning the update rules and learning rates…

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machine learning Research

Learning DAGs with Continuous Optimization

April 10, 2020

Can we build a bridge between the left and right hand side? As datasets continually increase in size and complexity, our ability to uncover meaningful insights from unstructured and unlabeled data is crucial. At the same time, a premium has…

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machine learning natural language processing Research

Are Sixteen Heads Really Better than One?

March 20, 2020

Since their inception in this 2017 paper by Vaswani et al., transformer models have become a staple of NLP research. They are used in machine translation, language modeling, and in general in most recent state-of-the-art pretrained models (Devlin et al.…

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machine learning Research

Inherent Tradeoffs in Learning Fair Representations

February 28, 2020

With the prevalence of machine learning applications in high-stakes domains (e.g., criminal judgment, medical testing, online advertising, etc.), it is crucial to ensure that these decision-support systems do not propagate existing bias or discrimination that might exist in historical data.…

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machine learning Research

RL for Planning and Planning for RL

February 13, 2020

The figure above illustrates the method:(a) Goal-conditioned RL often fails to reach distant goals, but can successfully reach the goal if starting nearby (inside the green region). (b) Our goal is to use observations in our replay buffer (yellow squares)…

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machine learning Research

RoboNet: A Dataset for Large-Scale Multi-Robot Learning

November 26, 2019

In the last decade, we’ve seen learning-based systems provide transformative solutions for a wide range of perception and reasoning problems, from recognizing objects in images to recognizing and translating human speech. Recent progress in deep reinforcement learning (i.e. integrating deep…

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