most citedAdaptive Learning for the Resource-Constrained Classification Problem

16 citations · 29 across the 3 of their papers we have counts for

collaborators

6 papers

cs.LG2022★ 16 cited

Adaptive Learning for the Resource-Constrained Classification Problem

Danit Shifman Abukasis, Izack Cohen, Xiaochen Xian +2

Resource-constrained classification tasks are common in real-world applications such as allocating tests for disease diagnosis, hiring decisions when filling a limited number of po…

cs.LG2022

SKTR: Trace Recovery from Stochastically Known Logs

Eli Bogdanov, Izack Cohen, Avigdor Gal

Developments in machine learning together with the increasing usage of sensor data challenge the reliance on deterministic logs, requiring new process mining solutions for uncertai…

cs.AI2022★ 13 cited

Conformance Checking Over Stochastically Known Logs

Eli Bogdanov, Izack Cohen, Avigdor Gal

With the growing number of devices, sensors and digital systems, data logs may become uncertain due to, e.g., sensor reading inaccuracies or incorrect interpretation of readings by…

cs.AI2021

Uncertain Process Data with Probabilistic Knowledge: Problem Characterization and Challenges

Izack Cohen, Avigdor Gal

Motivated by the abundance of uncertain event data from multiple sources including physical devices and sensors, this paper presents the task of relating a stochastic process obser…

cs.DC2021

Weighted completion time minimization for capacitated parallel machines

Ilan Reuven Cohen, Izack Cohen, Iyar Zaks

We consider the weighted completion time minimization problem for capacitated parallel machines, which is a fundamental problem in modern cloud computing environments. We study set…

math.OC2021

An adaptive robust optimization model for parallel machine scheduling

Izack Cohen, Krzysztof Postek, Shimrit Shtern

Real-life parallel machine scheduling problems can be characterized by: (i) limited information about the exact task duration at scheduling time, and (ii) an opportunity to resched…