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Transfer Learning for Reinforcement Learning Domains: A Survey

Transfer Learning for Reinforcement Learning Domains: A Survey. Matthew E. Taylor and Peter Stone. Journal of Machine Learning Research, 10(1):1633–1685, 2009.
Department of Computer Science - University of Texas at Austin

Vision Becomes Reality– Kristen Grauman Wins 2026 Hill Prize for Pioneering AI Research

Kristen Grauman, Ph.D., a professor in the Department of Computer Science, was awarded the prestigious 2026 Hill Prize in ...
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Academy for All

Experience programming, teamwork, and real-world applications in this week-long residential program for high school students. Choose from Arduino microcontrollers in the Standard Edition or Python in ...
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Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning

Abstract Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of ...
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UT Austin Students Earn Top Honors in Premier International Programming Contest

UT Programming Contests (UTPC) teams delivered a standout performance at the International Collegiate Programming Contest (ICPC) South Central Regional Competition on November 8, 2025. All four UT ...
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10 Computer Science Students Selected for New Amazon AI PhD Fellowship

Amazon just announced its new AI PhD Fellowship program, which will provide two years of funding for more than 100 PhD students at nine universities who are pursuing research on core AI disciplines ...
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Rectified Flow

Fig.2 - Rectified flow between π 0 (magenta contour) and π 1 (red contour). Green and blue lines are the trajectories colored based on which mode of π 0 they are associated with for visualization.
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UT Computer Science Ranked No. 9 Nationally, Top 10 in AI and Theory in U.S. News & World Report Rankings

The Department of Computer Science at The University of Texas at Austin ranks No. 9 nationally among undergraduate programs in the 2026 U.S. News & World Report Best Colleges rankings. Its Artificial ...
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Complexity Analysis

Some algorithms are more efficient than others. We would prefer to chose an efficient algorithm, so it would be nice to have metrics for comparing algorithm efficiency. The complexity of an algorithm ...
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Peter Stone to Lead UT Department of Computer Science as Chair, Emphasizing Continued Growth and Community

Prof. Peter Stone is a luminary in the Department of Computer Science, where he has been a faculty member for 23 years. Over the course of his tenure, he has been a firsthand witness to the rapid ...
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UT Expands Research on AI Accuracy and Reliability

Big news from UTCS: With renewed funding from the National Science Foundation, IFML researchers are expanding their work to make AI more accurate, reliable, and ready for the real world. This critical ...