Institution profile

PSL Research University

Academic institutioneurope · fr
Official website
Research library411linked papers
Opportunities0open roles
Selected work

Representative Papers

Monte Carlo Graph Coloring

Apr 04, 2025Communications in Computer and Information Science

This work addresses the NP-hard large-scale graph coloring problem by systematically adapting Monte Carlo search (MCS) paradigms—specifically Nested Monte Carlo Search (NMCS) and Nested Rollout Policy Adaptation (NRPA)—to this classical combinatorial optimization task for the first time. We propose a graph-coloring-specific state representation, a structured action space modeling, and a conflict-aware heuristic rollout policy, integrated with greedy initialization, dynamic vertex ordering, and conflict-driven backtracking. Experimental evaluation on standard benchmark graphs demonstrates that our approach improves coloring quality by 12–23% over mainstream heuristics—including DSATUR, RLF, and TABUCOL—on instances with over 100 vertices. Moreover, it achieves superior computational efficiency compared to most metaheuristics and significantly surpasses the scalability limits of traditional exact algorithms.

18 citationsRead paper

Querying Inconsistent Prioritized Data with ORBITS: Algorithms, Implementation, and Experiments (Extended Abstract)

Feb 16, 2022Description Logics

This paper addresses inconsistent-tolerant query answering over prioritized knowledge bases—comprising logical theories, factual databases, and priority relations among conflicting facts. We systematically support query evaluation under three classical semantics—AR (cautious), IAR (intersection of all repairs), and brave—over two classes of optimal repair models: Pareto-optimal and completion-based repairs. Our key contribution is the first unified SAT encoding framework capable of handling arbitrary priority relations, enabling joint modeling and efficient solving for both repair classes and all three semantics. Based on this encoding, we implement ORBITS, a novel reasoning system. Experimental results demonstrate that ORBITS significantly outperforms baseline approaches across all semantics, highlighting the critical impact of semantic choice and solving strategy on performance. The work establishes a new paradigm for practical reasoning over inconsistent prioritized knowledge bases.

18 citationsRead paper

Minimum Stable Cut and Treewidth

Apr 27, 2021International Colloquium on Automata, Languages and Programming

This paper studies the Minimum Stable Cut problem on graphs—i.e., finding a locally optimal cut of minimum weight, where no single-vertex reassignment improves the cut weight. We investigate its computational complexity and algorithm design under the dual parameters treewidth (tw) and maximum degree (Δ). We present the first FPT exact algorithm parameterized by tw and Δ, running in $2^{O(Delta cdot tw)}(n + log W)^{O(1)}$ time. We establish ETH-tight lower bounds: unless ETH fails, no $(nW)^{o(pw)}$ or $2^{o(Delta cdot pw)}$ algorithm exists. For unweighted graphs, we give an optimal $Delta^{O(tw)} n^{O(1)}$ algorithm. Moreover, we devise the first FPT approximation scheme, circumventing NP-hardness. Our techniques integrate dynamic programming over tree decompositions, pathwidth-based analysis, pseudo-polynomial encoding, and fine-grained ETH reductions.

7 citationsRead paper

Hierarchical Clustering of Complex Energy Systems Using Pretopology

Nov 27, 2025SMARTGREENS/VEHITS

Modeling and automatically classifying energy consumption patterns across large-scale distributed regional buildings remains challenging due to spatial heterogeneity, temporal dynamics, and limited physical interpretability. Method: This paper proposes a multi-criteria hierarchical clustering method grounded in pre-topological space properties. It jointly models energy consumption profiles using spatial, temporal, and statistical features; employs pre-topological structures to encode shape and connectivity; and integrates Pearson correlation analysis for multi-dimensional feature fusion. An open-source Python library is developed to support point-set, time-series, and real-world energy data processing. Contribution/Results: The work pioneers the application of pre-topology to energy pattern recognition, enhancing both clustering accuracy and physical interpretability. Experiments demonstrate exact spatial cluster recovery on synthetic data, perfect time-series clustering (adjusted Rand index = 1.0), and robust grouping of 400 real-world energy sites—enabling a new paradigm for intelligent, low-intervention energy management.

2 citationsRead paper

Parameterized Spanning Tree Congestion

Oct 10, 2024International Symposium on Mathematical Foundations of Computer Science

This paper studies the Tree Congestion Minimization problem: given a graph (G = (V,E)), compute a spanning tree (T) minimizing the maximum number of vertex-pair unique paths in (T) traversing any single edge—i.e., the edge congestion. While known to be NP-hard, its parameterized complexity remained open for years. We resolve this by proving, under the Exponential Time Hypothesis (ETH), that the problem is not fixed-parameter tractable (FPT) with respect to treewidth. Using a novel generic reduction framework, we establish W[1]-hardness with respect to stronger or incomparable structural parameters—including tree-depth plus feedback vertex set, and twin cover. Furthermore, we show NP-completeness even on graphs with maximum degree (Delta = 8) and modular width (mathrm{mw} = 4). These results comprehensively settle multiple long-standing open questions and significantly advance the theoretical boundaries of structural parameterized algorithms.

2 citationsRead paper
Recent publications

Latest Papers