b'Margo Seltzer'

research

∙ 09/17/2023

OSmosis: No more Déjà vu in OS isolation

Operating systems provide an abstraction layer between the hardware and ...

0 Sidhartha Agrawal, et al. ∙

research

∙ 06/19/2023

CAT-Walk: Inductive Hypergraph Learning via Set Walks

Temporal hypergraphs provide a powerful paradigm for modeling time-depen...

0 Ali Behrouz, et al. ∙

research

∙ 03/28/2023

Understanding and Exploring the Whole Set of Good Sparse Generalized Additive Models

In real applications, interaction between machine learning model and dom...

0 Zhi Chen, et al. ∙

research

∙ 11/15/2022

Anomaly Detection in Multiplex Dynamic Networks: from Blockchain Security to Brain Disease Prediction

The problem of identifying anomalies in dynamic networks is a fundamenta...

0 Ali Behrouz, et al. ∙

research

∙ 10/13/2022

Fast Optimization of Weighted Sparse Decision Trees for use in Optimal Treatment Regimes and Optimal Policy Design

Sparse decision trees are one of the most common forms of interpretable ...

7 Ali Behrouz, et al. ∙

research

∙ 10/12/2022

FasterRisk: Fast and Accurate Interpretable Risk Scores

Over the last century, risk scores have been the most popular form of pr...

9 Jiachang Liu, et al. ∙

research

∙ 09/19/2022

TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization

Given thousands of equally accurate machine learning (ML) models, how ca...

6 Zijie J. Wang, et al. ∙

research

∙ 09/16/2022

Exploring the Whole Rashomon Set of Sparse Decision Trees

In any given machine learning problem, there may be many models that cou...

1 Rui Xin, et al. ∙

research

∙ 02/23/2022

Fast Sparse Classification for Generalized Linear and Additive Models

We present fast classification techniques for sparse generalized linear ...

6 Jiachang Liu, et al. ∙

research

∙ 01/12/2022

Gridiron: A Technique for Augmenting Cloud Workloads with Network Bandwidth Requirements

Cloud applications use more than just server resources, they also requir...

0 Nodir Kodirov, et al. ∙

research

∙ 12/01/2021

How Smart Guessing Strategies Can Yield Massive Scalability Improvements for Sparse Decision Tree Optimization

Sparse decision tree optimization has been one of the most fundamental p...

3 Hayden McTavish, et al. ∙

research

∙ 08/26/2020

SIGL: Securing Software Installations Through Deep Graph Learning

Many users implicitly assume that software can only be exploited after i...

0 Xueyuan Han, et al. ∙

research

∙ 06/19/2020

The EuroSys 2020 Online Conference: Experience and lessons learned

The 15th European Conference on Computer Systems (EuroSys'20) was organi...

0 Angelos Bilas, et al. ∙

research

∙ 06/15/2020

Generalized Optimal Sparse Decision Trees

Decision tree optimization is notoriously difficult from a computational...

9 Jimmy Lin, et al. ∙

research

∙ 06/09/2020

Parking Packet Payload with P4

Network Function (NF) deployments suffer from poor link goodput, because...

0 Swati Goswami, et al. ∙

research

∙ 05/10/2020

Xanthus: Push-button Orchestration of Host Provenance Data Collection

Host-based anomaly detectors generate alarms by inspecting audit logs fo...

0 Xueyuan Han, et al. ∙

research

∙ 01/06/2020

UNICORN: Runtime Provenance-Based Detector for Advanced Persistent Threats

Advanced Persistent Threats (APTs) are difficult to detect due to their ...

0 Xueyuan Han, et al. ∙

research

∙ 09/24/2019

ProvMark: A Provenance Expressiveness Benchmarking System

System level provenance is of widespread interest for applications such ...

0 Sheung Chi Chan, et al. ∙

research

∙ 07/31/2019

Aquarium Technical Report Preprint

In this technical report, we present the core calculi for two of the dom...

0 Ming Kawaguchi, et al. ∙

research

∙ 04/29/2019

Optimal Sparse Decision Trees

Decision tree algorithms have been among the most popular algorithms for...

6 Xiyang Hu, et al. ∙

research

∙ 08/18/2018

Runtime Analysis of Whole-System Provenance

Identifying the root cause and impact of a system intrusion remains a fo...

0 Thomas Pasquier, et al. ∙

research

∙ 07/29/2018

Automatic Parallelization of Sequential Programs

Prior work on Automatically Scalable Computation (ASC) suggests that it ...

0 Peter Kraft, et al. ∙

research

∙ 06/04/2018

Provenance-based Intrusion Detection: Opportunities and Challenges

Intrusion detection is an arms race; attackers evade intrusion detection...

0 Xueyuan Han, et al. ∙

research

∙ 03/09/2018

Persistent Memory Transactions

This paper presents a comprehensive analysis of performance trade offs b...

0 Virendra Marathe, et al. ∙

research

∙ 11/30/2017

FRAPpuccino: Fault-detection through Runtime Analysis of Provenance

We present FRAPpuccino (or FRAP), a provenance-based fault detection mec...

0 Xueyuan Han, et al. ∙

research

∙ 11/14/2017

Practical Whole-System Provenance Capture

Data provenance describes how data came to be in its present form. It in...

0 Thomas Pasquier, et al. ∙

research

∙ 04/06/2017

Learning Certifiably Optimal Rule Lists for Categorical Data

We present the design and implementation of a custom discrete optimizati...

0 Elaine Angelino, et al. ∙

research

∙ 02/27/2016

Scalable Bayesian Rule Lists

We present an algorithm for building probabilistic rule lists that is tw...

0 Hongyu Yang, et al. ∙

research

∙ 03/28/2014

Accelerating MCMC via Parallel Predictive Prefetching

We present a general framework for accelerating a large class of widely ...

0 Elaine Angelino, et al. ∙

Margo Seltzer

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