Machine Learning Blog | ML@CMU | Carnegie Mellon University

deep learning machine learning machine translation natural language processing Research

On Learning Language-Invariant Representations for Universal Machine Translation

October 23, 2020

Despite the recent improvements in neural machine translation (NMT), training a large NMT model with hundreds of millions of parameters usually requires a collection of parallel corpora at a large scale, on the order of millions or even billions of…

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FATE machine learning Research

FACT Diagnostic: How to Better Understand Trade-offs Involving Group Fairness

October 12, 2020

The FACT diagnostic is a general framework that allows easier and flexible analyses of trade-offs between group fairness and predictive performance (type-1 trade-off), or among different types of group fairness definitions (type-2 trade-off)…

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artificial intelligence machine learning reinforcement learning Research

Plan2Explore: Active Model-Building for Self-Supervised Visual Reinforcement Learning

October 6, 2020

To operate successfully in unstructured open-world environments, autonomous intelligent agents need to solve many different tasks and learn new tasks quickly. Reinforcement learning has enabled artificial agents to solve complex tasks both in simulation and real world. However, it requires…

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deep learning machine learning Research

Generalizing Randomized Smoothing for Pointwise-Certified Defenses to Data Poisoning Attacks

September 25, 2020

Adversarial examples—targeted, human-imperceptible modifications to a test input that cause a deep network to fail catastrophically—have taken the machine learning community by storm, with a large body of literature dedicated to understanding and preventing this phenomenon (see these surveys). Understanding…

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Educational machine learning

F19 – Topics in data analysis

August 31, 2020

What is data analysis? A simple definition is: the application of machine learning and statistical methods to real world data to solve a problem. While this statement is simple, data analysis eventually requires expertise from a vast number of disciplines…

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machine learning Research

High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks

August 14, 2020

There are many works aiming to explain the generalization behavior of neural networks using heavy mathematical machinery, but we will do something different here: with a simple and intuitive twist of data, we will show that many generalization mysteries (like…

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machine learning Research

Maintaining the Illusion of Reality:
Transfer in RL by Keeping Agents in the DARC

July 31, 2020

Reinforcement learning (RL) is often touted as a promising approach for costly and risk-sensitive applications, yet practicing and learning in those domains directly is expensive. It costs time (e.g., OpenAI’s Dota2 project used 10,000 years of experience), it costs money…

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machine learning Research

In defense of weight-sharing for neural architecture search: an optimization perspective

July 17, 2020

Neural architecture search (NAS) -- selecting which neural model to use for your learning problem -- is a promising but computationally expensive direction for automating and democratizing machine learning. The weight-sharing method, whose initial success at dramatically accelerating NAS surprised…

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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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