Filters








7 Hits in 0.48 sec

Hamiltonicity in Semi-Regular Tessellation Dual Graphs [article]

Divya Gopinath, Rohan Kodialam, Kevin Lu, Jayson Lynch, Santiago Ospina
2019 arXiv   pre-print
This paper shows NP-completeness for finding Hamiltonian cycles in induced subgraphs of the dual graphs of semi-regular tessilations. It also shows NP-hardness for a new, wide class of graphs called augmented square grids. This work follows up on prior studies of the complexity of finding Hamiltonian cycles in regular and semi-regular grid graphs.
arXiv:1909.13755v1 fatcat:374ku2ki3rdbpkxlnqew36yjv4

Deep Contextual Clinical Prediction with Reverse Distillation [article]

Rohan S. Kodialam, Rebecca Boiarsky, Justin Lim, Neil Dixit, Aditya Sai, David Sontag
2020 arXiv   pre-print
Healthcare providers are increasingly using machine learning to predict patient outcomes to make meaningful interventions. However, despite innovations in this area, deep learning models often struggle to match performance of shallow linear models in predicting these outcomes, making it difficult to leverage such techniques in practice. In this work, motivated by the task of clinical prediction from insurance claims, we present a new technique called Reverse Distillation which pretrains deep
more » ... els by using high-performing linear models for initialization. We make use of the longitudinal structure of insurance claims datasets to develop Self Attention with Reverse Distillation, or SARD, an architecture that utilizes a combination of contextual embedding, temporal embedding and self-attention mechanisms and most critically is trained via reverse distillation. SARD outperforms state-of-the-art methods on multiple clinical prediction outcomes, with ablation studies revealing that reverse distillation is a primary driver of these improvements. Code is available at https://github.com/clinicalml/omop-learn.
arXiv:2007.05611v2 fatcat:c5gmxfxcnva47fm5gxvyaqkope

Competitive Algorithms for an Online Rent or Buy Problem with Variable Demand

Rohan Kodialam
2014 SIAM Undergraduate Research Online  
We consider a generalization of the classical Ski Rental Problem motivated by applications in cloud computing. We develop deterministic and probabilistic online algorithms for rent/buy decision problems with time-varying demand. We show that these algorithms have competitive ratios of 2 and 1.582 respectively. We also further establish the optimality of these algorithms. 233
doi:10.1137/14s013032 fatcat:wypjrahiujhc7lwyaj77cat5ce

Optimal Algorithms for Ski Rental with Soft Machine-Learned Predictions [article]

Rohan Kodialam
2019 arXiv   pre-print
We consider a variant of the classic Ski Rental online algorithm with applications to machine learning. In our variant, we allow the skier access to a black-box machine-learning algorithm that provides an estimate of the probability that there will be at most a threshold number of ski-days. We derive a class of optimal randomized algorithms to determine the strategy that minimizes the worst-case expected competitive ratio for the skier given a prediction from the machine learning algorithm,and
more » ... nalyze the performance and robustness of these algorithms.
arXiv:1903.00092v2 fatcat:q5mhbndbwvcwrarguo7bbjzlfi

Secure detection with correlated binary sensors

Rohan Chabukswar, Bruno Sinopoli
2015 2015 American Control Conference (ACC)  
Kodialam and Lakshman [14] also modeled intrusion detection as a zero-sum game, albeit between the service provider and the intruder.  ...  Rohan Chabukswar was with the Department of Electrical and Computer Engineering of Carnegie Mellon University, Pittsburgh, PA, United States when this work was done. rohanchabukswar@gmail.com Bruno Sinopoli  ... 
doi:10.1109/acc.2015.7171934 dblp:conf/amcc/ChabukswarS15 fatcat:yigjwvo57nco3kyd44u7fzxada

Secure Detection Using Binary Sensors

Rohan Chabukswar, Yilin Mo, Bruno Sinopoli
2013 IFAC Proceedings Volumes  
Kodialam and Lakshman (2003) also modeled intrusion detection as a zero-sum game, albeit between the service provider and the intruder.  ... 
doi:10.3182/20130925-2-de-4044.00033 fatcat:fe6uqb7e4fe2vmgdxne6tsngqa

Secure Detection in Cyberphysical Control Systems

Rohan Chabukswar
2018
Kodialam and Lakshman ([48] ) also modeled intrusion detection as a zero-sum game, albeit between the service provider and the intruder.  ... 
doi:10.1184/r1/6721439 fatcat:pnct2xvhrbdivgkuha5stujh7y