Publications (11)
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups
Sourya Basu, Suhas Lohit, Matthew Brand
Group equivariance is a strong inductive bias useful in a wide range of deep learning tasks. However, constructing efficient equivariant networks for general groups and domains is…
TuneComp: Joint Fine-tuning and Compression for Large Foundation Models
Xiangyu Chen, Jing Liu, Ye Wang +4
To reduce model size during post-training, compression methods, including knowledge distillation, low-rank approximation, and pruning, are often applied after fine-tuning the model…
Embedding Morphology into Transformers for Cross-Robot Policy Learning
Kei Suzuki, Jing Liu, Ye Wang +4
Cross-robot policy learning -- training a single policy to perform well across multiple embodiments -- remains a central challenge in robot learning. Transformer-based policies, su…
SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules
Xiangyu Chen, Jing Liu, Ye Wang +4
Low-rank adaptation (LoRA) and its variants are widely employed in fine-tuning large models, including large language models for natural language processing and diffusion models fo…
Marginalizing Out Future Passengers in Group Elevator Control
Daniel N. Nikovski, Matthew Brand
Group elevator scheduling is an NP-hard sequential decision-making problem with unbounded state spaces and substantial uncertainty. Decision-theoretic reasoning plays a surprisingl…
Choosing 1 of N with and without lucky numbers
Matthew Brand
How many fair coin tosses to choose 1 of options with uniform probability? Although a probability problem, the solution is essentially number-theoretic, with special roles for…