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X-WR-CALNAME:Bridge theory and practice: One-step full gradient could suffi
 ce for low-rank fine-tuning in LLMs\, provably and efficiently - Fanghui L
 iu\, Assistant Professor\, Warwick University
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TZID:America/Vancouver
TZUNTIL:20270314T100000Z
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DTSTART:20241103T020000
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
RDATE:20251102T020000
RDATE:20261101T020000
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RDATE:20260308T020000
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DTSTAMP:20260307T143552Z
CLASS:PUBLIC
CREATED:20250704T230846Z
DESCRIPTION:Abstract: In this talk\, I will talk about how theory can guide
  practice exemplified by low-rank fine-tuning (LoRA) in large language mod
 els. Our theory demonstrates that LoRA naturally aligns with a specific si
 ngular subspace of the one-step gradient from full fine-tuning. This cruci
 al insight motivated our development of a spectral initialization strategy
  that precisely targets and achieves this subspace alignment from the outs
 et. This strategy is not only theoretically optimal for subspace alignment
  but also allows for effective fine-tuning with just a single full gradien
 t step. We'll…
DTSTART;TZID=America/Vancouver:20250721T110000
DTEND;TZID=America/Vancouver:20250721T120000
LAST-MODIFIED:20250704T231259Z
LOCATION:UBC Vancouver Campus\, ICCS X836
SUMMARY:Bridge theory and practice: One-step full gradient could suffice fo
 r low-rank fine-tuning in LLMs\, provably and efficiently - Fanghui Liu\, 
 Assistant Professor\, Warwick University
TRANSP:OPAQUE
URL:https://caida.ubc.ca/event/bridge-theory-and-practice-one-step-full-gra
 dient-could-suffice-low-rank-fine-tuning-llms
END:VEVENT
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