Stratis Ioannidis

research

∙ 09/08/2023

Online Submodular Maximization via Online Convex Optimization

We study monotone submodular maximization under general matroid constrai...

0 Tareq Si Salem, et al. ∙

research

∙ 06/01/2023

Towards Bias Correction of FedAvg over Nonuniform and Time-Varying Communications

Federated learning (FL) is a decentralized learning framework wherein a ...

0 Ming Xiang, et al. ∙

research

∙ 05/10/2023

Multiverse at the Edge: Interacting Real World and Digital Twins for Wireless Beamforming

Creating a digital world that closely mimics the real world with its man...

0 Batool Salehi, et al. ∙

research

∙ 04/30/2023

DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning

Rehearsal-based approaches are a mainstay of continual learning (CL). Th...

0 Zifeng Wang, et al. ∙

research

∙ 04/16/2023

Explanations of Black-Box Models based on Directional Feature Interactions

As machine learning algorithms are deployed ubiquitously to a variety of...

0 Aria Masoomi, et al. ∙

research

∙ 03/17/2023

Stochastic Submodular Maximization via Polynomial Estimators

In this paper, we study stochastic submodular maximization problems with...

0 Gozde Ozcan, et al. ∙

research

∙ 02/06/2023

Jointly Optimal Routing and Caching with Bounded Link Capacities

We study a cache network in which intermediate nodes equipped with cache...

0 Yuanyuan Li, et al. ∙

research

∙ 01/26/2023

AlignGraph: A Group of Generative Models for Graphs

It is challenging for generative models to learn a distribution over gra...

0 Kimia Shayestehfard, et al. ∙

research

∙ 10/09/2022

Pruning Adversarially Robust Neural Networks without Adversarial Examples

Adversarial pruning compresses models while preserving robustness. Curre...

17 Tong Jian, et al. ∙

research

∙ 02/19/2022

Differentially Private Regression with Unbounded Covariates

We provide computationally efficient, differentially private algorithms ...

0 Jason Milionis, et al. ∙

research

∙ 01/13/2022

Experimental Design Networks: A Paradigm for Serving Heterogeneous Learners under Networking Constraints

Significant advances in edge computing capabilities enable learning to o...

0 Yuezhou Liu, et al. ∙

research

∙ 01/12/2022

Deep Learning on Multimodal Sensor Data at the Wireless Edge for Vehicular Network

Beam selection for millimeter-wave links in a vehicular scenario is a ch...

111 Batool Salehi, et al. ∙

research

∙ 06/20/2021

Robust Regression via Model Based Methods

The mean squared error loss is widely used in many applications, includi...

0 Armin Moharrer, et al. ∙

research

∙ 06/04/2021

Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness

We investigate the HSIC (Hilbert-Schmidt independence criterion) bottlen...

0 Zifeng Wang, et al. ∙

research

∙ 05/04/2021

On the Sample Complexity of Rank Regression from Pairwise Comparisons

We consider a rank regression setting, in which a dataset of N samples w...

0 Berkan Kadioglu, et al. ∙

research

∙ 02/15/2021

Machine Learning on Camera Images for Fast mmWave Beamforming

Perfect alignment in chosen beam sectors at both transmit- and receive-n...

45 Batool Salehi, et al. ∙

research

∙ 01/29/2021

No-Regret Caching via Online Mirror Descent

We study an online caching problem in which requests can be served by a ...

0 Tareq Si Salem, et al. ∙

research

∙ 01/19/2021

Submodular Maximization via Taylor Series Approximation

We study submodular maximization problems with matroid constraints, in p...

0 Gozde Ozcan, et al. ∙

research

∙ 01/09/2021

Rate Allocation and Content Placement in Cache Networks

We introduce the problem of optimal congestion control in cache networks...

0 Khashayar Kamran, et al. ∙

research

∙ 12/13/2020

Open-World Class Discovery with Kernel Networks

We study an Open-World Class Discovery problem in which, given labeled t...

0 Zifeng Wang, et al. ∙

research

∙ 12/13/2020

Learn-Prune-Share for Lifelong Learning

In lifelong learning, we wish to maintain and update a model (e.g., a ne...

0 Zifeng Wang, et al. ∙

research

∙ 09/21/2020

Bandits Under The Influence (Extended Version)

Recommender systems should adapt to user interests as the latter evolve....

0 Silviu Maniu, et al. ∙

research

∙ 11/22/2019

SIFO: Secure Computational Infrastructure using FPGA Overlays

Secure Function Evaluation (SFE) has received recent attention due to th...

0 Xin Fang, et al. ∙

research

∙ 09/08/2019

Iterative Spectral Method for Alternative Clustering

Given a dataset and an existing clustering as input, alternative cluster...

0 Chieh Wu, et al. ∙

research

∙ 08/09/2019

Deep Kernel Learning for Clustering

We propose a deep learning approach for discovering kernels tailored to ...

38 Chieh Wu, et al. ∙

research

∙ 04/16/2019

DeepRadioID: Real-Time Channel-Resilient Optimization of Deep Learning-based Radio Fingerprinting Algorithms

Radio fingerprinting provides a reliable and energy-efficient IoT authen...

0 Francesco Restuccia, et al. ∙

research

∙ 01/18/2019

Accelerated Experimental Design for Pairwise Comparisons

Pairwise comparison labels are more informative and less variable than c...

0 Yuan Guo, et al. ∙

research

∙ 01/14/2019

Kelly Cache Networks

We study networks of M/M/1 queues in which nodes act as caches that stor...

0 Milad Mahdian, et al. ∙

research

∙ 12/03/2018

ORACLE: Optimized Radio clAssification through Convolutional neuraL nEtworks

This paper describes the architecture and performance of ORACLE, an appr...

0 Kunal Sankhe, et al. ∙

research

∙ 11/06/2018

Deep feature transfer between localization and segmentation tasks

In this paper, we propose a new pre-training scheme for U-net based imag...

0 Szu-Yeu Hu, et al. ∙

research

∙ 09/15/2018

Time-Series Prediction of Proximal Aggression Onset in Minimally-Verbal Youth with Autism Spectrum Disorder Using Physiological Biosignals

It has been suggested that changes in physiological arousal precede pote...

0 Ozan Özdenizci, et al. ∙

research

∙ 04/27/2018

Intermediate Data Caching Optimization for Multi-Stage and Parallel Big Data Frameworks

In the era of big data and cloud computing, large amounts of data are ge...

0 Zhengyu Yang, et al. ∙

research

∙ 01/12/2018

A Family of Tractable Graph Distances

Important data mining problems such as nearest-neighbor search and clust...

0 José Bento, et al. ∙

research

∙ 08/22/2017

Learning Combinations of Sigmoids Through Gradient Estimation

We develop a new approach to learn the parameters of regression models w...

0 Stratis Ioannidis, et al. ∙

research

∙ 06/10/2015

Truthful Linear Regression

We consider the problem of fitting a linear model to data held by indivi...

0 Rachel Cummings, et al. ∙

research

∙ 08/09/2014

Guess Who Rated This Movie: Identifying Users Through Subspace Clustering

It is often the case that, within an online recommender system, multiple...

0 Amy Zhang, et al. ∙

research

∙ 11/11/2013

Learning Mixtures of Linear Classifiers

We consider a discriminative learning (regression) problem, whereby the ...

0 Yuekai Sun, et al. ∙

research

∙ 07/26/2012

Identifying Users From Their Rating Patterns

This paper reports on our analysis of the 2011 CAMRa Challenge dataset (...

0 José Bento, et al. ∙

research

∙ 06/18/2012

Comparison-Based Learning with Rank Nets

We consider the problem of search through comparisons, where a user is p...

0 Amin Karbasi, et al. ∙

research

∙ 07/15/2011

From Small-World Networks to Comparison-Based Search

The problem of content search through comparisons has recently received ...

0 Amin Karbasi, et al. ∙

Stratis Ioannidis

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