Date & Time: Venue: | December 26, 2024, 09:00 |
Candidate: | Daria Cherniuk |
PhD Program: | Computational and Data Science and Engineering |
Thesis Title: | Novel methods for quantization and acceleration of neural networks using efficient matrix representations |
Supervisor: | Professor Ivan Oseledets, Skoltech |
PhD Defense Jury Reports: | Professor Evgeny Burnaev, Skoltech (Chairman): report |
Revised thesis: | Novel methods for quantization and acceleration of neural networks using efficient matrix representations Thesis Changes Log (after minor revisions) |
PhD Defense Outcome: | Pass with Minor Revisions. The candidate’s thesis is accepted subject to minor revisions. The candidate made revisions to the thesis. The candidate is awarded the Skoltech PhD degree. |