3 papers
cs.LG2024
NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval
Sepanta Zeighami, Zac Wellmer, Aditya Parameswaran
-Nearest Neighbor search on dense vector embeddings (-NN retrieval) from pre-trained embedding models is the predominant retrieval method for text and images, as well as Retr…
cs.LG2021
Dropout's Dream Land: Generalization from Learned Simulators to Reality
Zac Wellmer, James T. Kwok
A World Model is a generative model used to simulate an environment. World Models have proven capable of learning spatial and temporal representations of Reinforcement Learning env…
cs.LG2019
Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space
Zac Wellmer, James Kwok
This paper proposes a novel deep reinforcement learning architecture that was inspired by previous tree structured architectures which were only useable in discrete action spaces.…