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Zhongdi Qu

6 accepted papers

2026

Unsupervised Combinatorial Probabilistic Reasoning: Probabilistic Coin Change Problem

Zhongdi Qu, Yingheng Wang, Utku Umur Acikalin, Aaron M. Ferber, Goncalo J. Gouveia, Brandon Bills +6
AAAI 2026technical

We introduce the Probabilistic Coin Change Problem (PCCP), a novel variant of the classical Combination Coin Change Problem (CCCP), motivated by a real-world scientific inverse task. The goal of CCCP is to enumerate all unordered combinations of coin denominations that sum to a given target. In PCCP

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2025

Constraint-aware Pareto Optimization for Tree-Structured Networks: Addressing Decarbonization Targets with Hydropower Expansion

Marc Grimson, Zhongdi Qu, Yue Mao, Aaron M Ferber, Felipe Siqueira Pacheco, Sebastian Heilpern +3
AAAI 2025technical

Addressing global sustainability challenges as outlined by the United Nations (UN) Sustainable Development Goals (SDGs) often requires navigating many potentially conflicting societal objectives simultaneously. For instance, increasing hydropower production enhances renewable energy supply but may a…

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2025

Expanding Connected Components from Alternative Terminals: Global Optimization for Freshwater Fishes Under the UN's 30x30 Conservation Goal

Yue Mao, Zhongdi Qu, Imanol Miqueleiz, Aaron Ferber, Sami Wolf, Marc Grimson +5
IJCAI 2025

Climate change and biodiversity loss are among humanity’s most pressing challenges. In 2022, under the auspices of the United Nations, over 190 countries reached a historic agreement to address the alarming loss of biodiversity and restore natural ecosystems. Target 3, often referred to as ``30x30''

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2023

From Understanding the Population Dynamics of the NSGA-II to the First Proven Lower Bounds

Benjamin Doerr, Zhongdi Qu
AAAI 2023technical

Due to the more complicated population dynamics of the NSGA-II, none of the existing runtime guarantees for this algorithm is accompanied by a non-trivial lower bound. Via a first mathematical understanding of the population dynamics of the NSGA-II, that is, by estimating the expected number of indi…

Cited by 41Source ↗PDF ↗Scholar ↗
2021

Translate & Fill: Improving Zero-Shot Multilingual Semantic Parsing with Synthetic Data

Massimo Nicosia, Zhongdi Qu, Yasemin Altun
EMNLP 2021finding

While multilingual pretrained language models (LMs) fine-tuned on a single language have shown substantial cross-lingual task transfer capabilities, there is still a wide performance gap in semantic parsing tasks when target language supervision is available. In this paper, we propose a novel Transl…

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