Publications

(2022). Learning and Optimization in Combinatorial Spaces with a Focus on Deep Learning for Vehicle Routing. PhD Thesis, 2022.

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(2022). Deep Policy Dynamic Programming for Vehicle Routing Problems. CPAIOR, 2022.

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(2022). A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning. TPAMI, 2022.

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(2022). Hybrid Genetic Search for the Vehicle Routing Problem with Time Windows: a High-Performance Implementation. DIMACS Workshop, 2022 VRPTW Winner.

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(2021). Unbiased Gradient Estimation with Balanced Assignments for Mixtures of Experts. NeurIPS ICBINB Workshop, 2021 Best Poster Award.

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(2020). Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement. JMLR 21(47), 2020.

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(2019). Estimating Gradients for Discrete Random Variables by Sampling without Replacement. ICLR 2020 Spotlight.

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(2019). Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement. ICML 2019 Honorable Mention.

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(2019). Buy 4 REINFORCE Samples, Get a Baseline for Free!. ICLR 2019 Deep RL meets Struct. Pred. Workshop.

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(2019). Attention, Learn to Solve Routing Problems!. ICLR 2019.

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(2014). Optimization of Two-Phase Methods using Simple Feedback Mechanisms. Master Thesis Best Thesis Award.

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(2014). ORTEC Pallet and Load Building. Master's Thesis, Business Analytics.

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(2013). Automation of the SET Card Game. Research Paper, Business Analytics.

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