2 citations · 3 across the 4 of their papers we have counts for
5 papers
Optimal Stopping with Gaussian Processes
Kshama Dwarakanath, Danial Dervovic, Peyman Tavallali +2
We propose a novel group of Gaussian Process based algorithms for fast approximate optimal stopping of time series with specific applications to financial markets. We show that str…
Deterministic Iteratively Built KD-Tree with KNN Search for Exact Applications
Aryan Naim, Joseph Bowkett, Sisir Karumanchi +2
K-Nearest Neighbors (KNN) search is a fundamental algorithm in artificial intelligence software with applications in robotics, and autonomous vehicles. These wide-ranging applicati…
Decision Theoretic Bootstrapping
Peyman Tavallali, Hamed Hamze Bajgiran, Danial J. Esaid +1
The design and testing of supervised machine learning models combine two fundamental distributions: (1) the training data distribution (2) the testing data distribution. Although t…
Adversarial Poisoning Attacks and Defense for General Multi-Class Models Based On Synthetic Reduced Nearest Neighbors
Pooya Tavallali, Vahid Behzadan, Peyman Tavallali +1
State-of-the-art machine learning models are vulnerable to data poisoning attacks whose purpose is to undermine the integrity of the model. However, the current literature on data…
Discrete linear-complexity reinforcement learning in continuous action spaces for Q-learning algorithms
Peyman Tavallali, Gary B. Doran, Lukas Mandrake
In this article, we sketch an algorithm that extends the Q-learning algorithms to the continuous action space domain. Our method is based on the discretization of the action space.…