Category: Machine learning
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New NSF grant to improve human-robot interaction
Drs. Matuszek, Ferraro and WInder received an NSF award for research on semi-supervised deep learning for domain adaptation in robotic language acquisition.
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JHU/APL CIRCUIT internship program information session, 3pm Fri 1/31
There will be a special information session on the JHU/APL CIRCUIT internship program from 3:00 pm to 4:30 pm on Friday, 31 January 2020 in room ITE 459.
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New NSF award will help robots learn to understand humans in complex environments
Prof. Ferraro in UMBC’s Pi2 visualization laboratory talking to a virtual robot, modeled using a combination of Unity, ROS, and Gazebo. Image from a recent paper on this research.. New NSF project will help robots learn to understand humans in complex environments UMBC Assistant Professor Cynthia Matuszek is the PI on a new NSF research…
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Prof. Oates receives NSF grant to develop distributed machine learning technology
Future machine learning systems will learn from multiple datasets without requiring that they be shared or consolodated in one location. UMBC CSEE Professor Tim Oates recently received a grant from NSF, “Truly Distributed Deep Learning: Representation and Computation”, to develop new architectures for deep learning systems that are distributed, allowing greater scale and control over…
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Meet Your Professor: Dr. Frank Ferraro, 12-1 Mon 3/25, ITE 239
Prof. Ferraro’s teaching and research areas include AI, language understanding and machine learning Meet Your Professor: Dr. Frank Ferraro Find out about Machine Learning and NLP classes 2:00-1:00 Monday, 25 March 2019, ITE 239 Next Monday, March 25th, join the Computer Science Education Club for its second installment of the “Meet Your Professor” Spring 2019…
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Maryland Data Science Conference, 1/14 CANCELED DUE TO WEATHER
MD Data Science Conference Monday, 14 January, UMBC Canceled due to Weather Miner & Kasch has decided to cancel the conference tomorrow due to the snow storm and reschedule it. “While around UMBC the snow seems to be letting up, we have several speakers and attendees from other areas that have raised concerns about…
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talk: Unbiased Decisions with Biased Data, Nov 14
Differential Fairness for Machine Learning and Artificial Intelligence Systems: Unbiased Decisions with Biased Data Prof. James Foulds Information Systems, UMBC 5:30-7:30 14 November 2018 MD-AI Meetup, Emerging Technology Centers, Baltimore With the rising influence of machine learning algorithms on many important aspects of our daily lives, there are growing concerns that biases inherent in…
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Machine learning and AI for cybersecurity: a technical chat with DISA
The UMBC Cyber Defense Lab Machine Learning and Artificial Intelligence: A Technical Chat with the Defense Information Systems Agency James Curry Lead Engineer–DoD Cyber Security Range Defense Information Systems Agency (DISA) 12:00–1:00pm Friday, 28 September 2018, ITE 227, UMBC A broad reaching brief on the scope and scale of the DISA Mission, followed by…
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2018 Mid-Atlantic Student Colloquium on Speech, Language and Learning
2018 Mid-Atlantic Student Colloquium on Speech, Language and Learning The 2018 Mid-Atlantic Student Colloquium on Speech, Language and Learning (MASC-SLL) is a student-run, one-day event on speech, language & machine learning research to be held at the University of Maryland, Baltimore County (UMBC) from 10:00am to 6:00pm on Saturday May 12. There is no registration charge…
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🗣 talk: Classifying Malware using Data Compression, 12-1 Fri 4/20, ITE229
The UMBC Cyber Defense Lab presents Classifying Malware using Data Compression Charles Nicholas, UMBC 12:00–1:00pm Friday, 20 April 2018, ITE 229 Comparing large binary objects can be tricky and expensive. We describe a method for comparing such strings, using ideas form data compression, that is both fast and effective. We present results from experiments applying…