25 citations · 143 across the 71 of their papers we have counts for
10 papers · 1 filter
Federated Myopic Community Detection with One-shot Communication
Chuyang Ke, Jean Honorio
In this paper, we study the problem of recovering the community structure of a network under federated myopic learning. Under this paradigm, we have several clients, each of them h…
A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning
Abi Komanduru, Jean Honorio
Inverse reinforcement learning (IRL) is the task of finding a reward function that generates a desired optimal policy for a given Markov Decision Process (MDP). This paper develops…
Information-Theoretic Bounds for Integral Estimation
Donald Q. Adams, Adarsh Barik, Jean Honorio
In this paper, we consider a zero-order stochastic oracle model of estimating definite integrals. In this model, integral estimation methods may query an oracle function for a fixe…
On the Fundamental Limits of Exact Inference in Structured Prediction
Hanbyul Lee, Kevin Bello, Jean Honorio
Inference is a main task in structured prediction and it is naturally modeled with a graph. In the context of Markov random fields, noisy observations corresponding to nodes and ed…
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem
Adarsh Barik, Jean Honorio
In this paper, we study the problem of fair sparse regression on a biased dataset where bias depends upon a hidden binary attribute. The presence of a hidden attribute adds an extr…
A Simple Unified Framework for High Dimensional Bandit Problems
Wenjie Li, Adarsh Barik, Jean Honorio
Stochastic high dimensional bandit problems with low dimensional structures are useful in different applications such as online advertising and drug discovery. In this work, we pro…
A Thorough View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy
Kevin Bello, Chuyang Ke, Jean Honorio
Performing inference in graphs is a common task within several machine learning problems, e.g., image segmentation, community detection, among others. For a given undirected connec…
Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees
Gregory Dexter, Kevin Bello, Jean Honorio
Inverse Reinforcement Learning (IRL) is the problem of finding a reward function which describes observed/known expert behavior. The IRL setting is remarkably useful for automated…
Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection
Jiajun Liang, Chuyang Ke, Jean Honorio
In this paper, we study the information theoretic bounds for exact recovery in sub-hypergraph models for community detection. We define a general model called the uniform sub-h…
Randomized Deep Structured Prediction for Discourse-Level Processing
Manuel Widmoser, Maria Leonor Pacheco, Jean Honorio +1
Expressive text encoders such as RNNs and Transformer Networks have been at the center of NLP models in recent work. Most of the effort has focused on sentence-level tasks, capturi…