Publications by Ilija Bogunovic

Adversarially Robust Optimization with Gaussian Processes

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

In this paper, we consider the problem of Gaussian process (GP) optimization with an added robustness requirement: The returned point may be perturbed by an adversary, and we require the function value to remain as high as possible even after this perturba ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

Volkan Cevher, Ilija Bogunovic, Slobodan Mitrovic, Ashkan Norouzi Fard, Jakub Tarnawski

We study the classical problem of maximizing a monotone submodular function subject to a cardinality constraint k, with two additional twists: (i) elements arrive in a streaming fashion and (ii) m items from the algorithm’s memory might be removed after th ...

2017

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Slobodan Mitrovic

We study the problem of maximizing a monotone submodular function subject to a cardinality constraint

k

, with the added twist that a number of items

\tau

from the returned set may be removed. We focus on the worst-case setting considered in Orlin et al ...

2017

A Distributed Algorithm for Partitioned Robust Submodular Maximization

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Slobodan Mitrovic

Abstract—In this paper, we consider the problem of maximizing a monotone submodular function subject to a cardinality constraint, with two added twists: The computation is distributed across a number of machines, and we require the solution to be robust ag ...

2017

Learning-based subsampling

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Yen-Huan Li, Luca Baldassarre, Baran Gözcü

The present invention concerns a method of sampling a test signal. The method comprises: acquiring (21) training signals sampled at a plurality of sampling locations; running (23) an optimization procedure for determining an index set of n indices, represe ...

2017

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

In this paper, we consider the problem of sequentially optimizing a black-box function

f

based on noisy samples and bandit feedback. We assume that

f

is smooth in the sense of having a bounded norm in some reproducing kernel Hilbert space (RKHS), yield ...

2017

An Efficient Streaming Algorithm for the Submodular Cover Problem

Volkan Cevher, Ilija Bogunovic, Ya-Ping Hsieh, Ashkan Norouzi Fard, Abbas Bazzi, Marwa El Halabi

We initiate the study of the classical Submodular Cover (SC) problem in the data streaming model which we refer to as the Streaming Submodular Cover (SSC). We show that any single pass streaming algorithm using sublinear memory in the size of the stream wi ...

2016

Time-Varying Gaussian Process Bandit Optimization

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

We consider the sequential Bayesian optimization problem with bandit feedback, adopting a formulation that allows for the reward function to vary with time. We model the reward function using a Gaussian process whose evolution obeys a simple Markov model. ...

2016

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

Volkan Cevher, Andreas Krause, Jonathan Mark Scarlett, Ilija Bogunovic

We present a new algorithm, truncated variance reduction (TruVaR), that treats Bayesian optimization (BO) and level-set estimation (LSE) with Gaussian processes in a unified fashion. The algorithm greedily shrinks a sum of truncated variances within a set ...

2016

Learning-Based Compressive Subsampling

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Yen-Huan Li, Luca Baldassarre, Baran Gözcü

The problem of recovering a structured signal

\mathbf{x} \in \mathbb{C}^p

from a set of dimensionality-reduced linear measurements

\mathbf{b} = \mathbf {A}\mathbf {x}

arises in a variety of applications, such as medical imaging, spectroscopy, Fourier o ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Ilija Bogunovic

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Adversarially Robust Optimization with Gaussian Processes

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

A Distributed Algorithm for Partitioned Robust Submodular Maximization

Learning-based subsampling

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

An Efficient Streaming Algorithm for the Submodular Cover Problem

Time-Varying Gaussian Process Bandit Optimization

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

Learning-Based Compressive Subsampling

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Robust Submodular Maximization: A Non-Uniform Partitioning Approach

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

A Distributed Algorithm for Partitioned Robust Submodular Maximization

Learning-based subsampling

An Efficient Streaming Algorithm for the Submodular Cover Problem

Adversarially Robust Optimization with Gaussian Processes

Time-Varying Gaussian Process Bandit Optimization

Learning-Based Compressive Subsampling