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09/12/2023
Long-term drought prediction using deep neural networks based on geospatial weather data
The accurate prediction of drought probability in specific regions is cr...
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02/16/2023
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow
The Gaussian Process (GP) based Chance-Constrained Optimal Power Flow (C...
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08/31/2022
Long-term hail risk assessment with deep neural networks
Hail risk assessment is necessary to estimate and reduce damage to crops...
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08/31/2022
Ranking-Based Physics-Informed Line Failure Detection in Power Grids
Climate change increases the number of extreme weather events (wind and ...
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08/30/2022
Data-Driven Chance Constrained AC-OPF using Hybrid Sparse Gaussian Processes
The alternating current (AC) chance-constrained optimal power flow (CC-O...
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07/21/2022
Data-Driven Stochastic AC-OPF using Gaussian Processes
In recent years, electricity generation has been responsible for more th...
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02/26/2022
Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation (Extended Abstract)
This paper is an extended version of [Burashnikova et al., 2021, arXiv: ...
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02/24/2022
Self-Training: A Survey
In recent years, semi-supervised algorithms have received a lot of inter...
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12/04/2021
Recommender systems: when memory matters
In this paper, we study the effect of long memory in the learnability of...
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11/23/2021
Importance sampling approach to chance-constrained DC optimal power flow
Despite significant economic and ecological effects, a higher level of r...
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12/12/2020
Learning over no-Preferred and Preferred Sequence of items for Robust Recommendation
In this paper, we propose a theoretically founded sequential strategy fo...
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10/22/2019
Tractable Minor-free Generalization of Planar Zero-field Ising Models
We present a new family of zero-field Ising models over N binary variabl...
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06/14/2019
A New Family of Tractable Ising Models
We present a new family of zero-field Ising models over N binary variabl...
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02/21/2019
Sequential Learning over Implicit Feedback for Robust Large-Scale Recommender Systems
In this paper, we propose a robust sequential learning strategy for trai...
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01/03/2019
Learning a Generator Model from Terminal Bus Data
In this work we investigate approaches to reconstruct generator models f...
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12/22/2018
Inference and Sampling of K_33-free Ising Models
We call an Ising model tractable when it is possible to compute its part...
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11/12/2018
Gauges, Loops, and Polynomials for Partition Functions of Graphical Models
We suggest a new methodology for analysis and approximate computations o...
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10/20/2017
Belief Propagation Min-Sum Algorithm for Generalized Min-Cost Network Flow
Belief Propagation algorithms are instruments used broadly to solve grap...
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10/19/2017
Importance sampling the union of rare events with an application to power systems analysis
This paper presents a method for estimating the probability μ of a union...
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04/29/2017
Representation Learning and Pairwise Ranking for Implicit Feedback in Recommendation Systems
In this paper, we propose a novel ranking framework for collaborative fi...
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01/23/2017
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification
We address the problem of multi-class classification in the case where t...
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07/02/2016