activity
20132026
most citedBuilding Programmable Wireless Networks: An Architectural Survey

28 citations · 41 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2026

Active Query Synthesis for Preference Learning

Namrata Nadagouda, Nauman Ahad, Maegan Tucker +1

Efficient learning of user preferences is crucial for many modern decision making systems but typically requires costly labeled data. Active learning reduces this cost, yet standar…

cs.LG2023★ 4 cited

Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis

Mehdi Azabou, Michael Mendelson, Nauman Ahad +4

Natural behavior consists of dynamics that are complex and unpredictable, especially when trying to predict many steps into the future. While some success has been found in buildin…

cs.CV2023★ 1 cited

MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction

Jorge Quesada, Lakshmi Sathidevi, Ran Liu +10

There are multiple scales of abstraction from which we can describe the same image, depending on whether we are focusing on fine-grained details or a more global attribute of the i…

stat.ME2022

Data-Adaptive Symmetric CUSUM for Sequential Change Detection

Nauman Ahad, Mark A. Davenport, Yao Xie

Detecting change points sequentially in a streaming setting, especially when both the mean and the variance of the signal can change, is often a challenging task. A key difficulty…

cs.LG2022★ 1 cited

Learning Behavior Representations Through Multi-Timescale Bootstrapping

Mehdi Azabou, Michael Mendelson, Maks Sorokin +4

Natural behavior consists of dynamics that are both unpredictable, can switch suddenly, and unfold over many different timescales. While some success has been found in building rep…

cs.LG2022★ 2 cited

Learning Sinkhorn divergences for supervised change point detection

Nauman Ahad, Eva L. Dyer, Keith B. Hengen +2

Many modern applications require detecting change points in complex sequential data. Most existing methods for change point detection are unsupervised and, as a consequence, lack a…

cs.LG2021★ 5 cited

Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time

Feng Zhu, Andrew R. Sedler, Harrison A. Grier +5

Modern neural interfaces allow access to the activity of up to a million neurons within brain circuits. However, bandwidth limits often create a trade-off between greater spatial s…

cs.LG2020

Semi-supervised sequence classification through change point detection

Nauman Ahad, Mark A. Davenport

Sequential sensor data is generated in a wide variety of practical applications. A fundamental challenge involves learning effective classifiers for such sequential data. While dee…

cs.NI2013★ 28 cited

Building Programmable Wireless Networks: An Architectural Survey

Junaid Qadir, Nadeem Ahmed, Nauman Ahad

In recent times, there have been a lot of efforts for improving the ossified Internet architecture in a bid to sustain unstinted growth and innovation. A major reason for the perce…