Company Filing History:
Years Active: 2022-2025
Title: Yash Chandak: Innovator in Reinforcement Learning
Introduction
Yash Chandak is a prominent inventor based in Amherst, MA (US). He has made significant contributions to the field of reinforcement learning, holding a total of 3 patents. His work focuses on generating proposed digital actions in high-dimensional action spaces, which has important implications for client devices.
Latest Patents
Chandak's latest patents include innovative systems and methods for decision-making processes. One of his notable patents is titled "Generating and providing proposed digital actions in high-dimensional action spaces using reinforcement learning models." This patent describes a system that utilizes supervised machine learning to train a latent representation decoder, enabling the determination of proposed digital actions based on latent representations. The system can identify the current state of a client device and generate a latent representation to propose digital actions from a set of available options.
Another significant patent is "Reinforcement learning with a stochastic action set." This patent outlines a decision-making process that incorporates actions characterized by stochastic availability. It provides a Markov decision process (MDP) model that includes a stochastic action set, allowing for the computation of a policy function based on the stochasticity of the actions available.
Career Highlights
Yash Chandak is currently employed at Adobe, Inc., where he continues to develop innovative solutions in the realm of machine learning and artificial intelligence. His work at Adobe has allowed him to apply his expertise in reinforcement learning to real-world applications, enhancing the capabilities of client devices.
Collaborations
Chandak collaborates with Georgios Theocharous, a fellow innovator in the field. Their partnership has led to advancements in the development of reinforcement learning models and their applications.
Conclusion
Yash Chandak is a notable inventor whose work in reinforcement learning is paving the way for advancements in digital action generation. His contributions to the field are significant, and his patents reflect a deep understanding of complex decision-making processes.