activity
20122024
most citedObtaining Calibrated Probabilities from Boosting

156 citations · 193 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024★ 1 cited

MCTR: Multi Camera Tracking Transformer

Alexandru Niculescu-Mizil, Deep Patel, Iain Melvin

Multi-camera tracking plays a pivotal role in various real-world applications. While end-to-end methods have gained significant interest in single-camera tracking, multi-camera tra…

cs.CV2021★ 1 cited

Hopper: Multi-hop Transformer for Spatiotemporal Reasoning

Honglu Zhou, Asim Kadav, Farley Lai +4

This paper considers the problem of spatiotemporal object-centric reasoning in videos. Central to our approach is the notion of object permanence, i.e., the ability to reason about…

cs.LG2020★ 2 cited

Supervised Feature Subset Selection and Feature Ranking for Multivariate Time Series without Feature Extraction

Shuchu Han, Alexandru Niculescu-Mizil

We introduce supervised feature ranking and feature subset selection algorithms for multivariate time series (MTS) classification. Unlike most existing supervised/unsupervised feat…

stat.ML2013★ 3 cited

Controlling the Precision-Recall Tradeoff in Differential Dependency Network Analysis

Diane Oyen, Alexandru Niculescu-Mizil, Rachel Ostroff +2

Graphical models have gained a lot of attention recently as a tool for learning and representing dependencies among variables in multivariate data. Often, domain scientists are loo…

cs.LG2012★ 156 cited

Obtaining Calibrated Probabilities from Boosting

Alexandru Niculescu-Mizil, Richard A. Caruana

Boosted decision trees typically yield good accuracy, precision, and ROC area. However, because the outputs from boosting are not well calibrated posterior probabilities, boosting…

cs.LG2012★ 30 cited

A Binary Classification Framework for Two-Stage Multiple Kernel Learning

Abhishek Kumar, Alexandru Niculescu-Mizil, Koray Kavukcuoglu +1

With the advent of kernel methods, automating the task of specifying a suitable kernel has become increasingly important. In this context, the Multiple Kernel Learning (MKL) proble…