189 citations · 393 across the 18 of their papers we have counts for
6 papers · 1 filter
MusicRL: Aligning Music Generation to Human Preferences
Geoffrey Cideron, Sertan Girgin, Mauro Verzetti +11
We propose MusicRL, the first music generation system finetuned from human feedback. Appreciation of text-to-music models is particularly subjective since the concept of musicality…
Data Summarization via Bilevel Optimization
Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi +1
The increasing availability of massive data sets poses a series of challenges for machine learning. Prominent among these is the need to learn models under hardware or human resour…
Semi-supervised Batch Active Learning via Bilevel Optimization
Zalán Borsos, Marco Tagliasacchi, Andreas Krause
Active learning is an effective technique for reducing the labeling cost by improving data efficiency. In this work, we propose a novel batch acquisition strategy for active learni…
Coresets via Bilevel Optimization for Continual Learning and Streaming
Zalán Borsos, Mojmír Mutný, Andreas Krause
Coresets are small data summaries that are sufficient for model training. They can be maintained online, enabling efficient handling of large data streams under resource constraint…
Transfer NAS: Knowledge Transfer between Search Spaces with Transformer Agents
Zalán Borsos, Andrey Khorlin, Andrea Gesmundo
Recent advances in Neural Architecture Search (NAS) have produced state-of-the-art architectures on several tasks. NAS shifts the efforts of human experts from developing novel arc…
Online Variance Reduction with Mixtures
Zalán Borsos, Sebastian Curi, Kfir Y. Levy +1
Adaptive importance sampling for stochastic optimization is a promising approach that offers improved convergence through variance reduction. In this work, we propose a new framewo…