1 citations · 1 across the 2 of their papers we have counts for
6 papers
Mitigating Negative Side Effects via Environment Shaping
Sandhya Saisubramanian, Shlomo Zilberstein
Agents operating in unstructured environments often produce negative side effects (NSE), which are difficult to identify at design time. While the agent can learn to mitigate the s…
Learning to Generate Fair Clusters from Demonstrations
Sainyam Galhotra, Sandhya Saisubramanian, Shlomo Zilberstein
Fair clustering is the process of grouping similar entities together, while satisfying a mathematically well-defined fairness metric as a constraint. Due to the practical challenge…
Balancing the Tradeoff Between Clustering Value and Interpretability
Sandhya Saisubramanian, Sainyam Galhotra, Shlomo Zilberstein
Graph clustering groups entities -- the vertices of a graph -- based on their similarity, typically using a complex distance function over a large number of features. Successful in…
Minimizing the Negative Side Effects of Planning with Reduced Models
Sandhya Saisubramanian, Shlomo Zilberstein
Reduced models of large Markov decision processes accelerate planning by considering a subset of outcomes for each state-action pair. This reduction in reachable states leads to re…
Lexicographically Ordered Multi-Objective Clustering
Sainyam Galhotra, Sandhya Saisubramanian, Shlomo Zilberstein
We introduce a rich model for multi-objective clustering with lexicographic ordering over objectives and a slack. The slack denotes the allowed multiplicative deviation from the op…
Planning in Stochastic Environments with Goal Uncertainty
Sandhya Saisubramanian, Kyle Hollins Wray, Luis Pineda +1
We present the Goal Uncertain Stochastic Shortest Path (GUSSP) problem -- a general framework to model path planning and decision making in stochastic environments with goal uncert…