b'Sanjay Chawla'

research

∙ 06/21/2023

Towards Mobility Data Science (Vision Paper)

Mobility data captures the locations of moving objects such as humans, a...

0 Mohamed Mokbel, et al. ∙

research

∙ 11/29/2022

A3T: Accuracy Aware Adversarial Training

Adversarial training has been empirically shown to be more prone to over...

0 Enes Altinisik, et al. ∙

research

∙ 11/20/2022

Interpretable Scientific Discovery with Symbolic Regression: A Review

Symbolic regression is emerging as a promising machine learning method f...

0 Nour Makke, et al. ∙

research

∙ 11/10/2022

Impact of Adversarial Training on Robustness and Generalizability of Language Models

Adversarial training is widely acknowledged as the most effective defens...

0 Enes Altinisik, et al. ∙

research

∙ 01/07/2022

Offline Reinforcement Learning for Road Traffic Control

Traffic signal control is an important problem in urban mobility with a ...

16 Mayuresh Kunjir, et al. ∙

research

∙ 10/13/2021

Updating Street Maps using Changes Detected in Satellite Imagery

Accurately maintaining digital street maps is labor-intensive. To addres...

0 Favyen Bastani, et al. ∙

research

∙ 04/02/2021

Permutation-Invariant Subgraph Discovery

We introduce Permutation and Structured Perturbation Inference (PSPI), a...

0 Raghvendra Mall, et al. ∙

research

∙ 12/22/2020

Probabilistic Outlier Detection and Generation

A new method for outlier detection and generation is introduced by lifti...

0 Stefano Giovanni Rizzo, et al. ∙

research

∙ 10/07/2020

QarSUMO: A Parallel, Congestion-optimized Traffic Simulator

Traffic simulators are important tools for tasks such as urban planning ...

0 Hao Chen, et al. ∙

research

∙ 09/17/2020

Understanding Effects of Editing Tweets for News Sharing by Media Accounts through a Causal Inference Framework

To reach a broader audience and optimize traffic toward news articles, m...

0 Kunwoo Park, et al. ∙

research

∙ 08/06/2020

Unravelling the Architecture of Membrane Proteins with Conditional Random Fields

In this paper, we will show that the recently introduced graphical model...

14 Lior Lukov, et al. ∙

research

∙ 07/19/2020

Sat2Graph: Road Graph Extraction through Graph-Tensor Encoding

Inferring road graphs from satellite imagery is a challenging computer v...

18 Songtao He, et al. ∙

research

∙ 12/28/2019

RoadTagger: Robust Road Attribute Inference with Graph Neural Networks

Inferring road attributes such as lane count and road type from satellit...

10 Songtao He, et al. ∙

research

∙ 06/17/2019

Machine-Assisted Map Editing

Mapping road networks today is labor-intensive. As a result, road maps h...

10 Favyen Bastani, et al. ∙

research

∙ 05/22/2019

AI-CARGO: A Data-Driven Air-Cargo Revenue Management System

We propose AI-CARGO, a revenue management system for air-cargo that comb...

0 Stefano Giovanni Rizzo, et al. ∙

research

∙ 01/10/2019

Deep Learning for Anomaly Detection: A Survey

Anomaly detection is an important problem that has been well-studied wit...

0 Raghavendra Chalapathy, et al. ∙

research

∙ 05/29/2018

Building your Cross-Platform Application with RHEEM

Today, organizations typically perform tedious and costly tasks to juggl...

0 Sanjay Chawla, et al. ∙

research

∙ 05/09/2018

RHEEMix in the Data Jungle -- A Cross-Platform Query Optimizer --

In pursuit of efficient and scalable data analytics, the insight that "o...

0 Sebastian Kruse, et al. ∙

research

∙ 04/13/2018

Group Anomaly Detection using Deep Generative Models

Unlike conventional anomaly detection research that focuses on point ano...

0 Raghavendra Chalapathy, et al. ∙

research

∙ 02/18/2018

Anomaly Detection using One-Class Neural Networks

We propose a one-class neural network (OC-NN) model to detect anomalies ...

1 Raghavendra Chalapathy, et al. ∙

research

∙ 02/11/2018

Unthule: An Incremental Graph Construction Process for Robust Road Map Extraction from Aerial Images

The availability of highly accurate maps has become crucial due to the i...

0 Favyen Bastani, et al. ∙

research

∙ 02/07/2018

Road Network Fusion for Incremental Map Updates

In the recent years a number of novel, automatic map-inference technique...

0 Rade Stanojevic, et al. ∙

research

∙ 01/31/2018

Optimizing Non-decomposable Measures with Deep Networks

We present a class of algorithms capable of directly training deep neura...

0 Amartya Sanyal, et al. ∙

research

∙ 12/25/2017

SAGA: A Submodular Greedy Algorithm For Group Recommendation

In this paper, we propose a unified framework and an algorithm for the p...

0 Shameem A Puthiya Parambath, et al. ∙

research

∙ 11/03/2017

SPARK: Static Program Analysis Reasoning and Retrieving Knowledge

Program analysis is a technique to reason about programs without executi...

0 Wasuwee Sodsong, et al. ∙

research

∙ 04/22/2017

Robust, Deep and Inductive Anomaly Detection

PCA is a classical statistical technique whose simplicity and maturity h...

0 Raghavendra Chalapathy, et al. ∙

research

∙ 02/20/2017

Kharita: Robust Map Inference using Graph Spanners

The widespread availability of GPS information in everyday devices such ...

0 Rade Stanojevic, et al. ∙

research

∙ 10/06/2016

A Robust Framework for Classifying Evolving Document Streams in an Expert-Machine-Crowd Setting

An emerging challenge in the online classification of social media data ...

0 Muhammad Imran, et al. ∙

research

∙ 05/13/2016

Online Optimization Methods for the Quantification Problem

The estimation of class prevalence, i.e., the fraction of a population t...

0 Purushottam Kar, et al. ∙

research

∙ 07/20/2011

Online Anomaly Detection Systems Using Incremental Commute Time

Commute Time Distance (CTD) is a random walk based metric on graphs. CTD...

0 Nguyen Lu Dang Khoa, et al. ∙

Sanjay Chawla

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