Fault monitoring and correction in a walking robot using LMS filters. - Martin Mladenov; Michael Mock; Karl-Erwin Grosspietsch (WISES, 2008)

Discovering bits of place histories from people's activity traces. - Gennady L. Andrienko; Natalia V. Andrienko; Martin Mladenov; Michael Mock; Christian Pölitz (IEEE VAST, 2010)

Extracting Events from Spatial Time Series. - Gennady L. Andrienko; Natalia V. Andrienko; Martin Mladenov; Michael Mock; Christian Pölitz (IV, 2010)

On Lifted PageRank, Kalman Filter and Towards Lifted Linear Program Solving. - Babak Ahmadi; Martin Mladenov; Kristian Kersting; Scott Sanner (LWA, 2011)

Pairwise Markov Logic. - Daan Fierens; Kristian Kersting; Jesse Davis; Jian Chen; Martin Mladenov (ILP, 2012)

Lifted Linear Programming. - Martin Mladenov; Babak Ahmadi; Kristian Kersting (AISTATS, 2012)

Identifying Place Histories from Activity Traces with an Eye to Parameter Impact. - Gennady L. Andrienko; Natalia V. Andrienko; Martin Mladenov; Michael Mock; Christian Pölitz (IEEE Trans. Vis. Comput. Graph., 2012)

Lifted Inference via k-Locality. - Martin Mladenov; Kristian Kersting (StarAI@AAAI, 2013)

Exploiting symmetries for scaling loopy belief propagation and relational training. - Babak Ahmadi; Kristian Kersting; Martin Mladenov; Sriraam Natarajan (Mach. Learn., 2013)

Lifting Relational MAP-LPs using Cluster Signatures. - Udi Apsel; Kristian Kersting; Martin Mladenov (StarAI@AAAI, 2014)

Power Iterated Color Refinement. - Kristian Kersting; Martin Mladenov; Roman Garnett; Martin Grohe (AAAI, 2014)

Efficient Lifting of MAP LP Relaxations Using k-Locality. - Martin Mladenov; Kristian Kersting; Amir Globerson (AISTATS, 2014)

Dimension Reduction via Colour Refinement. - Martin Grohe; Kristian Kersting; Martin Mladenov; Erkal Selman (ESA, 2014)

Lifted Message Passing as Reparametrization of Graphical Models. - Martin Mladenov; Amir Globerson; Kristian Kersting (UAI, 2014)

Relational Linear Programs. - Kristian Kersting; Martin Mladenov; Pavel Tokmakov (CoRR, 2014)

Computer Science on the Move: Inferring Migration Regularities from the Web via Compressed Label Propagation. - Fabian Hadiji; Martin Mladenov; Christian Bauckhage; Kristian Kersting (IJCAI, 2015)

Equitable Partitions of Concave Free Energies. - Martin Mladenov; Kristian Kersting (UAI, 2015)

RELOOP: A Python-Embedded Declarative Language for Relational Optimization. - Martin Mladenov; Danny Heinrich; Leonard Kleinhans; Felix Gonsior; Kristian Kersting (AAAI Workshop: Declarative Learning Based Programming, 2016)

Lifted Convex Quadratic Programming. - Martin Mladenov; Leonard Kleinhans; Kristian Kersting (CoRR, 2016)

The Symbolic Interior Point Method. - Martin Mladenov; Vaishak Belle; Kristian Kersting (AAAI, 2017)

Lifted Inference for Convex Quadratic Programs. - Martin Mladenov; Leonard Kleinhans; Kristian Kersting (AAAI, 2017)

Logistic Markov Decision Processes. - Martin Mladenov; Craig Boutilier; Dale Schuurmans; Ofer Meshi; Gal Elidan; Tyler Lu (IJCAI, 2017)

Relational linear programming. - Kristian Kersting; Martin Mladenov; Pavel Tokmakov (Artif. Intell., 2017)

Planning and Learning with Stochastic Action Sets. - Craig Boutilier; Alon Cohen; Avinatan Hassidim; Yishay Mansour; Ofer Meshi; Martin Mladenov; Dale Schuurmans (IJCAI, 2018)

Efficient Symbolic Integration for Probabilistic Inference. - Samuel Kolb; Martin Mladenov; Scott Sanner; Vaishak Belle; Kristian Kersting (IJCAI, 2018)

Planning and Learning with Stochastic Action Sets. - Craig Boutilier; Alon Cohen; Amit Daniely; Avinatan Hassidim; Yishay Mansour; Ofer Meshi; Martin Mladenov; Dale Schuurmans (CoRR, 2018)

Advantage Amplification in Slowly Evolving Latent-State Environments. - Martin Mladenov; Ofer Meshi; Jayden Ooi; Dale Schuurmans; Craig Boutilier (IJCAI, 2019)

Empirical Bayes Regret Minimization. - Chih-Wei Hsu; Branislav Kveton; Ofer Meshi; Martin Mladenov; Csaba Szepesvári (CoRR, 2019)

RecSim: A Configurable Simulation Platform for Recommender Systems. - Eugene Ie; Chih-Wei Hsu; Martin Mladenov; Vihan Jain; Sanmit Narvekar; Jing Wang; Rui Wu 020; Craig Boutilier (CoRR, 2019)

Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach. - Martin Mladenov; Elliot Creager; Omer Ben-Porat; Kevin Swersky; Richard S. Zemel; Craig Boutilier (ICML, 2020)

Differentiable Meta-Learning of Bandit Policies. - Craig Boutilier; Chih-Wei Hsu; Branislav Kveton; Martin Mladenov; Csaba Szepesvári; Manzil Zaheer (NeurIPS, 2020)

Demonstrating Principled Uncertainty Modeling for Recommender Ecosystems with RecSim NG. - Martin Mladenov; Chih-Wei Hsu; Vihan Jain; Eugene Ie; Christopher Colby; Nicolas Mayoraz; Hubert Pham; Dustin Tran; Ivan Vendrov; Craig Boutilier (RecSys, 2020)

Differentiable Bandit Exploration. - Craig Boutilier; Chih-Wei Hsu; Branislav Kveton; Martin Mladenov; Csaba Szepesvári; Manzil Zaheer (CoRR, 2020)

Differentiable Meta-Learning in Contextual Bandits. - Branislav Kveton; Martin Mladenov; Chih-Wei Hsu; Manzil Zaheer; Csaba Szepesvári; Craig Boutilier (CoRR, 2020)

Meta-Thompson Sampling. - Branislav Kveton; Mikhail Konobeev; Manzil Zaheer; Chih-Wei Hsu; Martin Mladenov; Craig Boutilier; Csaba Szepesvári (ICML, 2021)

Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. - Ruohan Zhan; Konstantina Christakopoulou; Ya Le; Jayden Ooi; Martin Mladenov; Alex Beutel; Craig Boutilier; Ed H. Chi; Minmin Chen (WWW, 2021)

RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems. - Martin Mladenov; Chih-Wei Hsu; Vihan Jain; Eugene Ie; Christopher Colby; Nicolas Mayoraz; Hubert Pham; Dustin Tran; Ivan Vendrov; Craig Boutilier (CoRR, 2021)

An adversarial variational inference approach for travel demand calibration of urban traffic simulators. - Martin Mladenov; Sanjay Ganapathy Subramaniam; Chih-Wei Hsu; Neha Arora; Andrew Tomkins; Craig Boutilier; Carolina Osorio (SIGSPATIAL/GIS, 2022)

Reinforcement Learning with History Dependent Dynamic Contexts. - Guy Tennenholtz; Nadav Merlis; Lior Shani; Martin Mladenov; Craig Boutilier (ICML, 2023)

Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. - Abhishek Naik; Bo Chang 002; Alexandros Karatzoglou; Martin Mladenov; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2023)

Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics. - Guy Tennenholtz; Martin Mladenov; Nadav Merlis; Craig Boutilier (CoRR, 2023)

Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems. - Siddharth Prasad; Martin Mladenov; Craig Boutilier (CoRR, 2023)

Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models. - Craig Boutilier; Martin Mladenov; Guy Tennenholtz (CoRR, 2023)

Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization. - Craig Boutilier; Martin Mladenov; Guy Tennenholtz (AAAI, 2024)

Demystifying Embedding Spaces using Large Language Models. - Guy Tennenholtz; Yinlam Chow; Chih-Wei Hsu; Jihwan Jeong; Lior Shani; Azamat Tulepbergenov; Deepak Ramachandran; Martin Mladenov; Craig Boutilier (ICLR, 2024)

Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies. - Chih-Wei Hsu; Martin Mladenov; Ofer Meshi; James Pine; Hubert Pham; Shane Li; Xujian Liang; Anton Polishko; Li Yang; Ben Scheetz; Craig Boutilier (SIGIR, 2024)

Report on the Workshop on Simulations for Information Access (Sim4IA 2024) at SIGIR 2024. - Timo Breuer 002; Christin Katharina Kreutz; Norbert Fuhr; Krisztian Balog; Philipp Schaer; Nolwenn Bernard; Ingo Frommholz; Marcel Gohsen; Kaixin Ji; Gareth J. F. Jones; Jüri Keller; Jiqun Liu; et al. (CoRR, 2024)

Report on the 1st Workshop on Simulations for Information Access (Sim4IA 2024) at SIGIR 2024. - Timo Breuer 002; Christin Katharina Kreutz; Norbert Fuhr; Krisztian Balog; Philipp Schaer; Nolwenn Bernard; Ingo Frommholz; Marcel Gohsen; Kaixin Ji; Gareth J. F. Jones; Jüri Keller; Jiqun Liu; et al. (SIGIR Forum, 2024)

All that Glitters is not Gold: Uncovering Exposed Industrial Control Systems and Honeypots in the Wild. - Martin Mladenov; László Erdodi; Georgios Smaragdakis (EuroS&P, 2025)