the university of tennessee
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the university of tennessee
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machine intelligence lab |
| Danny Budik, M.Sc. EE | ||
| [ cv ] | ||
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[homepage] |
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| Research | Reinforcement Learning and Approximate Dynamic Programming | |
| Neural Networks | ||
| My research focused on FPGA-based architectures for large-scale recurrent neural networks. In particular, I studied real-time learning algorithms that lend themselves to hardware implementation on FPGA platforms. | ||
| Selected Publications | |
| [1] | D. Budik, I. Elhanany, "TRTRL: A Localized Resource-Efficient Learning Algorithm for Recurrent Neural Networks," 2006 IEEE International Midwest Symposium on Circuits & Systems (MWSCAS), San Juan, Puerto Rico, August, 2006 [pdf] |
