Výsledky vyhledávání - "Jayanta Mandi"

Contrastive Losses and Solution Caching for Predict-and-Optimize

Autor: Maxime Mulamba, Michelangelo Diligenti, Victor Bucarey, Tias Guns, Michele Lombardi, Jayanta Mandi

Publikováno v: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
IJCAI

Many decision-making processes involve solving a combinatorial optimization problem with uncertain input that can be estimated from historic data. Recently, problems in this class have been successfully addressed via end-to-end learning approaches, w

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87e4ec6713651d67247ada91db17db6c

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TSP with Learned Zone Preferences for Last-Mile Vehicle Dispatching

Autor: Rocsildes Canoy, Jayanta Mandi, Victor Bucarey Lopez, Emilio Gamba, Maxime Mulamba Ke Tchomba, Tias Guns

Publikováno v: Vrije Universiteit Brussel

In the spring of 2021, Amazon hosted the Last Mile Routing Research Challenge with support from the MIT Center for Transportation & Logistics. The goal of the challenge was to encourage participants to develop innovative approaches to produce solutio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::10b40f589265fdc20a50d835220fcd1b
https://hdl.handle.net/20.500.14017/fcbc115a-3bf9-4426-ba6c-333a15a0ea21

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Smart predict-and-optimize for hard combinatorial optimization problems

Autor: Emir Demirović, Peter J. Stuckey, Tias Guns, Jayanta Mandi

Publikováno v: Vrije Universiteit Brussel
AAAI

Combinatorial optimization assumes that all parameters of the optimization problem, e.g. the weights in the objective function, are fixed. Often, these weights are mere estimates and increasingly machine learning techniques are used to for their esti

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::190f66d09a81ffcf9111debce8fc7efc
https://lirias.kuleuven.be/handle/123456789/672960

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Hybrid Classification and Reasoning for Image-based Constraint Solving

Autor: Tias Guns, Maxime Mulamba, Jayanta Mandi, Rocsildes Canoy

Publikováno v: Integration of Constraint Programming, Artificial Intelligence, and Operations Research ISBN: 9783030589417
CPAIOR

There is an increased interest in solving complex constrained problems where part of the input is not given as facts, but received as raw sensor data such as images or speech. We will use ‘visual sudoku’ as a prototype problem, where the given ce

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b63085d2566b00b64585a46b6fcbad4
https://lirias.kuleuven.be/handle/123456789/672955

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Interior Point Solving for LP-based prediction+optimisation

Autor: Jayanta Mandi, Tias Guns

Publikováno v: Vrije Universiteit Brussel

Solving optimization problems is the key to decision making in many real-life analytics applications. However, the coefficients of the optimization problems are often uncertain and dependent on external factors, such as future demand or energy or sto

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Use of Artificial Intelligence to Analyse Risk in Legal Documents for a Better Decision Support

Autor: Jayanta Mandi, Nandini Roy, Satyaki Roy, Indranil Mitra, Neelam Patodia, Dipankar Chakrabarti, Udayan Bhattacharya, Prasun Nandy

Publikováno v: TENCON

Assessing risk for voluminous legal documents such as request for proposal, contracts is tedious and error prone. We have developed "risk-o-meter", a framework, based on machine learning and natural language processing to review and assess risks of a

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Entropy-Based Consumption Diversity—The Case of India

Autor: Jayanta Mandi, Manisha Chakrabarty

Publikováno v: Opportunities and Challenges in Development ISBN: 9789811399800

In recent years, there has been growing research in analysing the spending diversification of households in applied demand analysis using disaggregated household-level data. Taking cue from Engel’s (Die Lebenskosten Belgischer Arbeiter Familien frf

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f87fa902a1b4478586731b41519e9e05
https://doi.org/10.1007/978-981-13-9981-7_24

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Differentiable Optimization Layer with an Interior Point Approach

Autor: Jayanta Mandi, Tias Guns

Publikováno v: Vrije Universiteit Brussel

Combinatorial Optimization has wide applications throughout many industries. However, in many real-life applications, some or all coefficients of the optimization problem are not known at the time of execution. In such applications, those coefficient

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::64a4db733d7cf30ced2a60060028f7eb
https://researchportal.vub.be/en/publications/d79e1ef5-23a0-4e49-b58e-4b82592071ca

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Decision-Focused Learning: Through the Lens of Learning to Rank

Autor: Jayanta Mandi, Victor Bucarey Lopez, Maxime Mulamba Ke Tchomba, Tias Guns

Publikováno v: Vrije Universiteit Brussel

In the last years decision-focused learning framework, also known as predict-and-optimize, have received increasing attention. In this setting, the predictions of a machine learning model are used as estimated cost coefficients in the objective funct

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6962dd7940e7fff4e8faf5085c75ddd9
https://researchportal.vub.be/en/publications/bdcc758c-21f8-428b-af96-824860c61a13

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