3 citations · 7 across the 14 of their papers we have counts for
15 papers
Wiener Space Cubature for Nonlinear Gaussian Filtering
Luke Snow, Daniel Waxman, Matthew E. Levine
Continuous-discrete filtering is a classical problem in signal processing and control theory, whereby the state driving a stochastic differential equation (SDE) must be inferred fr…
Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning
Vikram Krishnamurthy, Luke Snow
Inverse reinforcement learning (IRL) recovers the loss function of a forward learner from its observed responses. Adaptive IRL aims to reconstruct the loss function of a forward le…
Efficient Counterfactual Estimation of Conditional Greeks via Malliavin-based Weak Derivatives
Vikram Krishnamurthy, Luke Snow
We study counterfactual gradient estimation of conditional loss functionals of diffusion processes. In quantitative finance, these gradients are known as conditional Greeks: the se…
Malliavin Calculus with Weak Derivatives for Counterfactual Stochastic Optimization
Vikram Krishnamurthy, Luke Snow
We study counterfactual stochastic optimization of conditional loss functionals under misspecified and noisy gradient information. The difficulty is that when the conditioning even…
Multi-Agent Inverse Reinforcement Learning for Identifying Pareto-Efficient Coordination -- A Distributionally Robust Approach
Luke Snow, Vikram Krishnamurthy
Multi-agent inverse reinforcement learning (IRL) aims to identify Pareto-efficient behavior in a multi-agent system, and reconstruct utility functions of the individual agents. Mot…
Multi-Agent Inverse Learning for Sensor Networks: Identifying Coordination in UAV Networks
Luke Snow, Vikram Krishnamurthy
Suppose there is an adversarial UAV network being tracked by a radar. How can the radar determine whether the UAVs are coordinating, in some well-defined sense? How can the radar i…
Efficient Neural SDE Training using Wiener-Space Cubature
Luke Snow, Vikram Krishnamurthy
A neural stochastic differential equation (SDE) is an SDE with drift and diffusion terms parametrized by neural networks. The training procedure for neural SDEs consists of optimiz…
Distributionally Robust Inverse Reinforcement Learning for Identifying Multi-Agent Coordinated Sensing
Luke Snow, Vikram Krishnamurthy
We derive a minimax distributionally robust inverse reinforcement learning (IRL) algorithm to reconstruct the utility functions of a multi-agent sensing system. Specifically, we co…
Data-Driven Mechanism Design via Multi-Agent Revealed Preferences
Luke Snow, Vikram Krishnamurthy
We study a sequence of independent one-shot non-cooperative games where agents play equilibria determined by a tunable mechanism. Observing only equilibrium decisions, without para…
Statistical Detection of Coordination in a Cognitive Radar Network through Inverse Multi-objective Optimization
Luke Snow, Vikram Krishnamurthy
Consider a target being tracked by a cognitive radar network. If the target can intercept noisy radar emissions, how can it detect coordination in the radar network? By 'coordinati…
Finite-Sample Bounds for Adaptive Inverse Reinforcement Learning using Passive Langevin Dynamics
Luke Snow, Vikram Krishnamurthy
This paper provides a finite-sample analysis of a passive stochastic gradient Langevin dynamics (PSGLD) algorithm. This algorithm is designed to achieve adaptive inverse reinforcem…
Identifying Coordination in a Cognitive Radar Network -- A Multi-Objective Inverse Reinforcement Learning Approach
Luke Snow, Vikram Krishnamurthy, Brian M. Sadler
Consider a target being tracked by a cognitive radar network. If the target can intercept some radar network emissions, how can it detect coordination among the radars? By 'coordin…
Quickest Detection for Human-Sensor Systems using Quantum Decision Theory
Luke Snow, Vikram Krishnamurthy, Brian M. Sadler
In mathematical psychology, recent models for human decision-making use Quantum Decision Theory to capture important human-centric features such as order effects and violation of t…
Lyapunov based Stochastic Stability of a Quantum Decision System for Human-Machine Interaction
Luke Snow, Shashwat Jain, Vikram Krishnamurthy
In mathematical psychology, decision makers are modeled using the Lindbladian equations from quantum mechanics to capture important human-centric features such as order effects and…
Lyapunov based Stochastic Stability of Human-Machine Interaction: A Quantum Decision System Approach
Luke Snow, Shashwat Jain, Vikram Krishnamurthy
In mathematical psychology, decision makers are modeled using the Lindbladian equations from quantum mechanics to capture important human-centric features such as order effects and…