5 papers
Tropical Reinforcement Learning
Arip Asadulaev, Aladin Djuhera, Karim Salta +3
Reinforcement learning for large language models typically maximizes expected return, adding up the probabilities of all successful trajectories. However, the classical sum formula…
Perturb-and-Solve: Efficient Learned-Operator Conditioning for Latent Diffusion Inverse Problems
Abduragim Shtanchaev, Arip Asadulaev, Luiza Labazanova +3
Latent diffusion models serve as powerful priors for solving inverse problems in image restoration, such as deblurring, inpainting, and super-resolution. Current methods have a tra…
Value-Gradient Hypothesis of RL for LLMs
Arip Asadulaev, Daniil Ognev, Karim Salta +1
Reinforcement learning substantially improves pretrained language models, but it remains understudied why critic-free methods such as PPO and GRPO work as well as they do, and when…
A Granular Grassmannian Clustering Framework via the Schubert Variety of Best Fit
Karim Salta, Michael Kirby, Chris Peterson
In many classification and clustering tasks, it is useful to compute a geometric representative for a dataset or a cluster, such as a mean or median. When datasets are represented…
A Multi-Domain Multi-Task Approach for Feature Selection from Bulk RNA Datasets
Karim Salta, Tomojit Ghosh, Michael Kirby
In this paper a multi-domain multi-task algorithm for feature selection in bulk RNAseq data is proposed. Two datasets are investigated arising from mouse host immune response to Sa…