Search Results for author: Hilaf Hasson

Found 6 papers, 1 papers with code

Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting

no code implementations25 May 2023 Hilaf Hasson, Danielle C. Maddix, Yuyang Wang, Gaurav Gupta, Youngsuk Park

Ensembling is among the most popular tools in machine learning (ML) due to its effectiveness in minimizing variance and thus improving generalization.

Time Series Time Series Forecasting

Testing Causality for High Dimensional Data

no code implementations14 Mar 2023 Arun Jambulapati, Hilaf Hasson, Youngsuk Park, Yuyang Wang

Determining causal relationship between high dimensional observations are among the most important tasks in scientific discoveries.

Vocal Bursts Intensity Prediction

Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms

1 code implementation19 Jul 2022 Linbo Liu, Youngsuk Park, Trong Nghia Hoang, Hilaf Hasson, Jun Huan

This work studies the threats of adversarial attack on multivariate probabilistic forecasting models and viable defense mechanisms.

Adversarial Attack Multivariate Time Series Forecasting +2

Probabilistic Forecasting: A Level-Set Approach

no code implementations NeurIPS 2021 Hilaf Hasson, Bernie Wang, Tim Januschowski, Jan Gasthaus

By recognizing the connection of our algorithm to random forests (RFs) and quantile regression forests (QRFs), we are able to prove consistency guarantees of our approach under mild assumptions on the underlying point estimator.

Time Series Time Series Analysis

Dynamic Regret for Strongly Adaptive Methods and Optimality of Online KRR

no code implementations22 Nov 2021 Dheeraj Baby, Hilaf Hasson, Yuyang Wang

When the loss functions are strongly convex or exp-concave, we demonstrate that Strongly Adaptive (SA) algorithms can be viewed as a principled way of controlling dynamic regret in terms of path variation $V_T$ of the comparator sequence.

Open-Ended Question Answering regression

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