30 citations · 89 across the 7 of their papers we have counts for
9 papers
Identifying Driver Interactions via Conditional Behavior Prediction
Ekaterina Tolstaya, Reza Mahjourian, Carlton Downey +3
Interactive driving scenarios, such as lane changes, merges and unprotected turns, are some of the most challenging situations for autonomous driving. Planning in interactive scena…
Learning and Inference in Hilbert Space with Quantum Graphical Models
Siddarth Srinivasan, Carlton Downey, Byron Boots
Quantum Graphical Models (QGMs) generalize classical graphical models by adopting the formalism for reasoning about uncertainty from quantum mechanics. Unlike classical graphical m…
Links: A High-Dimensional Online Clustering Method
Philip Andrew Mansfield, Quan Wang, Carlton Downey +2
We present a novel algorithm, called Links, designed to perform online clustering on unit vectors in a high-dimensional Euclidean space. The algorithm is appropriate when it is nec…
Speaker Diarization with LSTM
Quan Wang, Carlton Downey, Li Wan +2
For many years, i-vector based audio embedding techniques were the dominant approach for speaker verification and speaker diarization applications. However, mirroring the rise of d…
Predictive State Recurrent Neural Networks
Carlton Downey, Ahmed Hefny, Boyue Li +2
We present a new model, Predictive State Recurrent Neural Networks (PSRNNs), for filtering and prediction in dynamical systems. PSRNNs draw on insights from both Recurrent Neural N…
Practical Learning of Predictive State Representations
Carlton Downey, Ahmed Hefny, Geoffrey Gordon
Over the past decade there has been considerable interest in spectral algorithms for learning Predictive State Representations (PSRs). Spectral algorithms have appealing theoretica…
An Efficient, Expressive and Local Minima-free Method for Learning Controlled Dynamical Systems
Ahmed Hefny, Carlton Downey, Geoffrey J. Gordon
We propose a framework for modeling and estimating the state of controlled dynamical systems, where an agent can affect the system through actions and receives partial observations…
Supervised Learning for Dynamical System Learning
Ahmed Hefny, Carlton Downey, Geoffrey Gordon
Recently there has been substantial interest in spectral methods for learning dynamical systems. These methods are popular since they often offer a good tradeoff between computatio…
Large-scale randomized-coordinate descent methods with non-separable linear constraints
Sashank Reddi, Ahmed Hefny, Carlton Downey +2
We develop randomized (block) coordinate descent (CD) methods for linearly constrained convex optimization. Unlike most CD methods, we do not assume the constraints to be separable…