14 papers
Foundation Models for Event Prediction Across Heterogeneous Event Logs
Fabian Spaeh, Sean Jaffe, Shandian Zhe +1
Event logs are ubiquitous across real-world domains, including business processes, manufacturing workflows, healthcare, and many other operational systems. Yet event logs can diffe…
Universal Multi-Modal Traceformer: Integrating Heterogeneous Context for Process Event Prediction
Fabian Spaeh, Jingxing Fang, Shandian Zhe +1
Event logs arise in a wide range of real-world processes, capturing not only event activities and timestamps but also multi-modal contextual information. Existing event-sequence mo…
Efficient Algorithms for Influence Maximization in General Models and Observed Cascades
Fabian Spaeh, Themistoklis Haris, Alina Ene +1
We study influence maximization in general stochastic models, the observed cascades model, and the independent cascade (IC) model. For general stochastic models with only black-box…
Query Suggestion for Retrieval-Augmented Generation via Dynamic In-Context Learning
Fabian Spaeh, Tianyi Chen, Chen-Hao Chiang +1
Retrieval-augmented generation with tool-calling agents (agentic RAG) has become increasingly powerful in understanding, processing, and responding to user queries. However, the sc…
Estimating Hitting Times Locally At Scale
Themistoklis Haris, Fabian Spaeh, Spyros Dragazis +1
Hitting times provide a fundamental measure of distance in random processes, quantifying the expected number of steps for a random walk starting at node to reach node . They…
An Asymptotically Optimal Approximation Algorithm for Multiobjective Submodular Maximization at Scale
Fabian Spaeh, Atsushi Miyauchi
Maximizing a single submodular set function subject to a cardinality constraint is a well-studied and central topic in combinatorial optimization. However, finding a set that maxim…
Countering Election Sway: Strategic Algorithms in Friedkin-Johnsen Dynamics
Dragos Ristache, Fabian Spaeh, Charalampos E. Tsourakakis
Social influence profoundly impacts individual choices and collective behaviors in politics. In this work, driven by the goal of protecting elections from improper influence, we co…
Wiser than the Wisest of Crowds: The Asch Effect Revisited under Friedkin-Johnsen Opinion Dynamics
Dragos Ristache, Fabian Spaeh, Charalampos E. Tsourakakis
In 1907, Sir Francis Galton independently asked 787 villagers to estimate the weight of an ox. Although none of them guessed the exact weight, the average estimate was remarkably a…
ULTRA-MC: A Unified Approach to Learning Mixtures of Markov Chains via Hitting Times
Fabian Spaeh, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
This study introduces a novel approach for learning mixtures of Markov chains, a critical process applicable to various fields, including healthcare and the analysis of web users.…
Markovletics: Methods and A Novel Application for Learning Continuous-Time Markov Chain Mixtures
Fabian Spaeh, Charalampos E. Tsourakakis
Sequential data naturally arises from user engagement on digital platforms like social media, music streaming services, and web navigation, encapsulating evolving user preferences…
Online and Streaming Algorithms for Constrained -Submodular Maximization
Fabian Spaeh, Alina Ene, Huy L. Nguyen
Constrained -submodular maximization is a general framework that captures many discrete optimization problems such as ad allocation, influence maximization, personalized recomme…
Learning Mixtures of Markov Chains with Quality Guarantees
Fabian Spaeh, Charalampos E. Tsourakakis
A large number of modern applications ranging from listening songs online and browsing the Web to using a navigation app on a smartphone generate a plethora of user trails. Cluster…
Online Ad Allocation with Predictions
Fabian Spaeh, Alina Ene
Display Ads and the generalized assignment problem are two well-studied online packing problems with important applications in ad allocation and other areas. In both problems, ad i…
Global Evaluation for Decision Tree Learning
Fabian Spaeh, Sven Kosub
We transfer distances on clusterings to the building process of decision trees, and as a consequence extend the classical ID3 algorithm to perform modifications based on the global…