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ORCIDBoi Faltings
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- affiliation: Swiss Federal Institute of Technology in Lausanne, Switzerland
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2020 – today
- 2023
[j60]Christina Timko
, Malte Niederstadt, Naman Goel, Boi Faltings:
Incentive Mechanism Design for Responsible Data Governance: A Large-scale Field Experiment. ACM J. Data Inf. Qual. 15(2): 16:1-16:18 (2023)- [c263]Panayiotis Danassis, Aris Filos-Ratsikas, Haipeng Chen, Milind Tambe, Boi Faltings:
AI-driven Prices for Externalities and Sustainability in Production Markets. AAMAS 2023: 2463-2465 - [c262]Diego Antognini, Shuyang Li, Boi Faltings, Julian J. McAuley:
Assistive Recipe Editing through Critiquing. EACL 2023: 375-384 - [c261]Martin Josifoski, Maxime Peyrard, Frano Rajic, Jiheng Wei, Debjit Paul, Valentin Hartmann, Barun Patra, Vishrav Chaudhary, Emre Kiciman, Boi Faltings:
Language Model Decoding as Likelihood-Utility Alignment. EACL (Findings) 2023: 1425-1440 - [c260]Boi Faltings:
Game-theoretic Mechanisms for Eliciting Accurate Information. IJCAI 2023: 6601-6609 - [e4]Randy Goebel, Han Yu, Boi Faltings, Lixin Fan, Zehui Xiong:
Trustworthy Federated Learning - First International Workshop, FL 2022, Held in Conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13448, Springer 2023, ISBN 978-3-031-28995-8 [contents] - [i61]Debjit Paul, Mete Ismayilzada, Maxime Peyrard, Beatriz Borges, Antoine Bosselut, Robert West, Boi Faltings:
REFINER: Reasoning Feedback on Intermediate Representations. CoRR abs/2304.01904 (2023) - 2022
- [j59]Panayiotis Danassis, Zeki Doruk Erden, Boi Faltings:
Exploiting environmental signals to enable policy correlation in large-scale decentralized systems. Auton. Agents Multi Agent Syst. 36(1): 13 (2022) - [j58]Panayiotis Danassis, Marija Sakota, Aris Filos-Ratsikas, Boi Faltings:
Putting ridesharing to the test: efficient and scalable solutions and the power of dynamic vehicle relocation. Artif. Intell. Rev. 55(7): 5781-5844 (2022) - [j57]Aleksei Triastcyn, Boi Faltings:
Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees. Algorithms 15(7): 232 (2022) - [j56]Dimitris Chatzopoulos, Anurag Jain, Sujit Gujar, Boi Faltings, Pan Hui:
Toward Mobile Distributed Ledgers. IEEE Internet Things J. 9(11): 7891-7903 (2022) - [j55]Qiang Yang, Yongxin Tong, Yang Liu, Yangqiu Song, Hao Peng, Boi Faltings:
Introduction to the Special Issue on the Federated Learning: Algorithms, Systems, and Applications: Part 1. ACM Trans. Intell. Syst. Technol. 13(4): 52:1-52:3 (2022) - [j54]Qiang Yang, Yongxin Tong, Yang Liu, Yangqiu Song, Hao Peng, Boi Faltings:
Preface to Federated Learning: Algorithms, Systems, and Applications: Part 2. ACM Trans. Intell. Syst. Technol. 13(5): 69:1-69:2 (2022) - [c259]Panayiotis Danassis, Aleksei Triastcyn, Boi Faltings:
A Distributed Differentially Private Algorithm for Resource Allocation in Unboundedly Large Settings. AAMAS 2022: 327-335 - [c258]Fengyu Cai, Wanhao Zhou, Fei Mi, Boi Faltings:
Slim: Explicit Slot-Intent Mapping with Bert for Joint Multi-Intent Detection and Slot Filling. ICASSP 2022: 7607-7611 - [i60]Diego Antognini, Boi Faltings:
Positive and Negative Critiquing for VAE-based Recommenders. CoRR abs/2204.02162 (2022) - [i59]Diego Antognini, Shuyang Li, Boi Faltings, Julian J. McAuley:
Assistive Recipe Editing through Critiquing. CoRR abs/2205.02454 (2022) - [i58]Shuangqi Li, Diego Antognini, Boi Faltings:
Interlock-Free Multi-Aspect Rationalization for Text Classification. CoRR abs/2205.06756 (2022) - [i57]Ljubomir Rokvic, Panayiotis Danassis, Boi Faltings:
Privacy-preserving Data Filtering in Federated Learning Using Influence Approximation. CoRR abs/2205.11518 (2022) - [i56]Martin Josifoski, Maxime Peyrard, Frano Rajic, Jiheng Wei, Debjit Paul, Valentin Hartmann, Barun Patra, Vishrav Chaudhary, Emre Kiciman, Boi Faltings, Robert West:
Language Model Decoding as Likelihood-Utility Alignment. CoRR abs/2210.07228 (2022) - 2021
- [c257]Diego Antognini, Claudiu Musat, Boi Faltings:
Multi-Dimensional Explanation of Target Variables from Documents. AAAI 2021: 12507-12515 - [c256]Diego Antognini, Boi Faltings:
Rationalization through Concepts. ACL/IJCNLP (Findings) 2021: 761-775 - [c255]Panayiotis Danassis, Zeki Doruk Erden, Boi Faltings:
Improved Cooperation by Exploiting a Common Signal. AAMAS 2021: 395-403 - [c254]Fei Mi, Wanhao Zhou, Lingjing Kong, Fengyu Cai, Minlie Huang, Boi Faltings:
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems. EMNLP (1) 2021: 1887-1898 - [c253]Panayiotis Danassis, Florian Wiedemair, Boi Faltings:
Improving Multi-agent Coordination by Learning to Estimate Contention. IJCAI 2021: 125-131 - [c252]Diego Antognini, Claudiu Musat, Boi Faltings:
Interacting with Explanations through Critiquing. IJCAI 2021: 515-521 - [c251]Diego Antognini, Boi Faltings:
Fast Multi-Step Critiquing for VAE-based Recommender Systems. RecSys 2021: 209-219 - [c250]Milena Filipovic, Blagoj Mitrevski, Diego Antognini, Emma Lejal Glaude, Boi Faltings, Claudiu Musat:
Modeling Online Behavior in Recommender Systems: The Importance of Temporal Context. Perspectives@RecSys 2021 - [c249]Blagoj Mitrevski, Milena Filipovic, Emma Lejal Glaude, Boi Faltings, Claudiu Musat:
Momentum-based Gradient Methods in Multi-Objective Recommendation. MORS@RecSys 2021 - [c248]Diana Andreea Petrescu, Diego Antognini, Boi Faltings:
Multi-Step Critiquing User Interface for Recommender Systems. RecSys 2021: 760-763 - [c247]Kirtan Padh, Diego Antognini, Emma Lejal Glaude, Boi Faltings, Claudiu Musat:
Addressing fairness in classification with a model-agnostic multi-objective algorithm. UAI 2021: 600-609 - [c246]Sankarshan Damle, Aleksei Triastcyn, Boi Faltings, Sujit Gujar:
Differentially Private Multi-Agent Constraint Optimization. WI/IAT 2021: 422-429 - [c245]Sankarshan Damle, Boi Faltings, Sujit Gujar:
Blockchain-based Practical Multi-agent Secure Comparison and its Application in Auctions. WI/IAT 2021: 430-437 - [i55]Dimitris Chatzopoulos, Anurag Jain, Sujit Gujar, Boi Faltings, Pan Hui:
Towards Mobile Distributed Ledgers. CoRR abs/2101.04825 (2021) - [i54]Panayiotis Danassis, Zeki Doruk Erden, Boi Faltings:
Improved Cooperation by Exploiting a Common Signal. CoRR abs/2102.02304 (2021) - [i53]Diego Antognini, Boi Faltings:
Fast Multi-Step Critiquing for VAE-based Recommender Systems. CoRR abs/2105.00774 (2021) - [i52]Panayiotis Danassis, Florian Wiedemair, Boi Faltings:
Improving Multi-agent Coordination by Learning to Estimate Contention. CoRR abs/2105.04027 (2021) - [i51]Diego Antognini, Boi Faltings:
Rationalization through Concepts. CoRR abs/2105.04837 (2021) - [i50]Panayiotis Danassis, Aris Filos-Ratsikas, Boi Faltings:
Achieving Diverse Objectives with AI-driven Prices in Deep Reinforcement Learning Multi-agent Markets. CoRR abs/2106.06060 (2021) - [i49]Diana Petrescu, Diego Antognini, Boi Faltings:
Multi-Step Critiquing User Interface for Recommender Systems. CoRR abs/2107.06416 (2021) - [i48]Fengyu Cai, Wanhao Zhou, Fei Mi, Boi Faltings:
SLIM: Explicit Slot-Intent Mapping with BERT for Joint Multi-Intent Detection and Slot Filling. CoRR abs/2108.11711 (2021) - [i47]Fei Mi, Wanhao Zhou, Fengyu Cai, Lingjing Kong, Minlie Huang, Boi Faltings:
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems. CoRR abs/2108.12589 (2021) - [i46]Fei Mi, Tao Lin, Boi Faltings:
Representation Memorization for Fast Learning New Knowledge without Forgetting. CoRR abs/2108.12596 (2021) - 2020
- [j53]Aleksei Triastcyn, Boi Faltings:
Federated Generative Privacy. IEEE Intell. Syst. 35(4): 50-57 (2020) - [c244]Fei Mi, Lingjing Kong, Tao Lin, Kaicheng Yu, Boi Faltings:
Generalized Class Incremental Learning. CVPR Workshops 2020: 970-974 - [c243]Panayiotis Danassis, Boi Faltings:
Efficient Allocations in Constant Time: Towards Scalable Solutions in the Era of Large Scale Intelligent Systems. ECAI 2020: 2895-2896 - [c242]Moin Hussain Moti, Dimitris Chatzopoulos, Pan Hui, Boi Faltings, Sujit Gujar:
Orthos: A Trustworthy AI Framework for Data Acquisition. EMAS@AAMAS 2020: 100-118 - [c241]Fei Mi, Liangwei Chen, Mengjie Zhao, Minlie Huang, Boi Faltings:
Continual Learning for Natural Language Generation in Task-oriented Dialog Systems. EMNLP (Findings) 2020: 3461-3474 - [c240]Aleksei Triastcyn, Boi Faltings:
Bayesian Differential Privacy for Machine Learning. ICML 2020: 9583-9592 - [c239]Naman Goel, Aris Filos-Ratsikas, Boi Faltings:
Peer-Prediction in the Presence of Outcome Dependent Lying Incentives. IJCAI 2020: 124-131 - [c238]Fei Mi, Boi Faltings:
Memory Augmented Neural Model for Incremental Session-based Recommendation. IJCAI 2020: 2169-2176 - [c237]Naman Goel, Cyril van Schreven, Aris Filos-Ratsikas, Boi Faltings:
Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain. IJCAI 2020: 4604-4610 - [c236]Dimitris Chatzopoulos, Sujit Gujar, Boi Faltings, Pan Hui:
Mneme: A Mobile Distributed Ledger. INFOCOM 2020: 1897-1906 - [c235]Diego Antognini, Boi Faltings:
HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset. LREC 2020: 4917-4923 - [c234]Diego Antognini, Boi Faltings:
GameWikiSum: a Novel Large Multi-Document Summarization Dataset. LREC 2020: 6645-6650 - [c233]Fei Mi, Xiaoyu Lin, Boi Faltings:
ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation. RecSys 2020: 408-413 - [c232]Naman Goel, Maxime Rutagarama, Boi Faltings:
Tackling Peer-to-Peer Discrimination in the Sharing Economy. WebSci 2020: 355-361 - [p2]Adam Richardson, Aris Filos-Ratsikas, Boi Faltings:
Budget-Bounded Incentives for Federated Learning. Federated Learning 2020: 176-188 - [i45]Nikola Milojkovic, Diego Antognini, Giancarlo Bergamin, Boi Faltings, Claudiu Musat:
Multi-Gradient Descent for Multi-Objective Recommender Systems. CoRR abs/2001.00846 (2020) - [i44]Diego Antognini, Boi Faltings:
GameWikiSum: a Novel Large Multi-Document Summarization Dataset. CoRR abs/2002.06851 (2020) - [i43]Diego Antognini, Boi Faltings:
HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset. CoRR abs/2002.06854 (2020) - [i42]Aleksei Triastcyn, Boi Faltings:
Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees. CoRR abs/2003.00997 (2020) - [i41]Fei Mi, Boi Faltings:
Memory Augmented Neural Model for Incremental Session-based Recommendation. CoRR abs/2005.01573 (2020) - [i40]Diego Antognini, Claudiu Musat, Boi Faltings:
T-RECS: a Transformer-based Recommender Generating Textual Explanations and Integrating Unsupervised Language-based Critiquing. CoRR abs/2005.11067 (2020) - [i39]Fei Mi, Xiaoyu Lin, Boi Faltings:
ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation. CoRR abs/2007.12000 (2020) - [i38]Kirtan Padh, Diego Antognini, Emma Lejal Glaude, Boi Faltings, Claudiu Musat:
Addressing Fairness in Classification with a Model-Agnostic Multi-Objective Algorithm. CoRR abs/2009.04441 (2020) - [i37]Blagoj Mitrevski, Milena Filipovic, Diego Antognini, Emma Lejal Glaude, Boi Faltings, Claudiu Musat:
Momentum-based Gradient Methods in Multi-objective Recommender Systems. CoRR abs/2009.04695 (2020) - [i36]Milena Filipovic, Blagoj Mitrevski, Diego Antognini, Emma Lejal Glaude, Boi Faltings, Claudiu Musat:
Modeling Online Behavior in Recommender Systems: The Importance of Temporal Context. CoRR abs/2009.08978 (2020) - [i35]Fei Mi, Liangwei Chen, Mengjie Zhao, Minlie Huang, Boi Faltings:
Continual Learning for Natural Language Generation in Task-oriented Dialog Systems. CoRR abs/2010.00910 (2020) - [i34]Panayiotis Danassis, Aleksei Triastcyn, Boi Faltings:
Differential Privacy Meets Maximum-weight Matching. CoRR abs/2011.07934 (2020)
2010 – 2019
- 2019
- [c231]Naman Goel, Boi Faltings:
Deep Bayesian Trust: A Dominant and Fair Incentive Mechanism for Crowd. AAAI 2019: 1996-2003 - [c230]Stéphane Martin, Boi Faltings, Vincent Schickel:
Context-Tree Recommendation vs Matrix-Factorization: Algorithm Selection and Live Users Evaluation. AAAI 2019: 9534-9540 - [c229]Naman Goel, Boi Faltings:
Crowdsourcing with Fairness, Diversity and Budget Constraints. AIES 2019: 297-304 - [c228]Panayiotis Danassis, Boi Faltings:
Courtesy as a Means to Coordinate. AAMAS 2019: 665-673 - [c227]Sankarshan Damle, Boi Faltings, Sujit Gujar:
A Truthful, Privacy-Preserving, Approximately Efficient Combinatorial Auction For Single-minded Bidders. AAMAS 2019: 1916-1918 - [c226]Aleksei Triastcyn, Boi Faltings:
Federated Learning with Bayesian Differential Privacy. IEEE BigData 2019: 2587-2596 - [c225]Panayiotis Danassis, Aris Filos-Ratsikas, Boi Faltings:
Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior. IJCAI 2019: 215-222 - [c224]Fei Mi, Minlie Huang, Jiyong Zhang, Boi Faltings:
Meta-Learning for Low-resource Natural Language Generation in Task-oriented Dialogue Systems. IJCAI 2019: 3151-3157 - [c223]Naman Goel, Boi Faltings:
Personalized Peer Truth Serum for Eliciting Multi-Attribute Personal Data. UAI 2019: 18-27 - [i33]Aleksei Triastcyn, Boi Faltings:
Improved Accounting for Differentially Private Learning. CoRR abs/1901.09697 (2019) - [i32]Panayiotis Danassis, Aris Filos-Ratsikas, Boi Faltings:
Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior. CoRR abs/1902.09359 (2019) - [i31]Fei Mi, Minlie Huang, Jiyong Zhang, Boi Faltings:
Meta-Learning for Low-resource Natural Language Generation in Task-oriented Dialogue Systems. CoRR abs/1905.05644 (2019) - [i30]Sankarshan Damle, Boi Faltings, Sujit Gujar:
A Practical Solution to Yao's Millionaires' Problem and Its Application in Designing Secure Combinatorial Auction. CoRR abs/1906.06567 (2019) - [i29]Cyril van Schreven, Naman Goel, Boi Faltings:
Infochain: A Decentralized System for Truthful Information Elicitation. CoRR abs/1908.10258 (2019) - [i28]Adam Richardson, Aris Filos-Ratsikas, Boi Faltings:
Rewarding High-Quality Data via Influence Functions. CoRR abs/1908.11598 (2019) - [i27]Boi Faltings, Martin Charles Golumbic:
An Effective Upperbound on Treewidth Using Partial Fill-in of Separators. CoRR abs/1909.02789 (2019) - [i26]Diego Antognini, Claudiu Musat, Boi Faltings:
Multi-Dimensional Explanation of Reviews. CoRR abs/1909.11386 (2019) - [i25]Diego Antognini, Boi Faltings:
Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization. CoRR abs/1909.12231 (2019) - [i24]Aleksei Triastcyn, Boi Faltings:
Federated Generative Privacy. CoRR abs/1910.08385 (2019) - [i23]Aleksei Triastcyn, Boi Faltings:
Federated Learning with Bayesian Differential Privacy. CoRR abs/1911.10071 (2019) - [i22]Panayiotis Danassis, Marija Sakota, Aris Filos-Ratsikas, Boi Faltings:
Putting Ridesharing to the Test: Efficient and Scalable Solutions and the Power of Dynamic Vehicle Relocation. CoRR abs/1912.08066 (2019) - 2018
- [j52]Igor Kulev, Pearl Pu, Boi Faltings:
A Bayesian Approach to Intervention-Based Clustering. ACM Trans. Intell. Syst. Technol. 9(4): 44:1-44:23 (2018) - [c222]Goran Radanovic, Boi Faltings:
Partial Truthfulness in Minimal Peer Prediction Mechanisms With Limited Knowledge. AAAI 2018: 1595-1602 - [c221]Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings:
Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints. AAAI 2018: 1603-1610 - [c220]Naman Goel, Mohammad Yaghini, Boi Faltings:
Non-Discriminatory Machine Learning Through Convex Fairness Criteria. AAAI 2018: 3029-3036 - [c219]Panayiotis Danassis, Boi Faltings:
Learning in Ad-hoc Anti-coordination Scenarios. AAAI Spring Symposia 2018 - [c218]Naman Goel, Mohammad Yaghini, Boi Faltings:
Non-Discriminatory Machine Learning through Convex Fairness Criteria. AIES 2018: 116 - [c217]Dimitris Chatzopoulos, Sujit Gujar, Boi Faltings, Pan Hui:
Privacy Preserving and Cost Optimal Mobile Crowdsensing Using Smart Contracts on Blockchain. MASS 2018: 442-450 - [c216]Stéphane Martin, Boi Faltings, Vincent Schickel:
Enhancing Session-Based Recommendations through Sequential Modeling. UMAP 2018: 359-360 - [i21]Panayiotis Danassis, Boi Faltings:
A Courteous Learning Rule for Ad-hoc Anti-coordination. CoRR abs/1801.07140 (2018) - [i20]Aleksei Triastcyn, Boi Faltings:
Generating Differentially Private Datasets Using GANs. CoRR abs/1803.03148 (2018) - [i19]Naman Goel, Boi Faltings:
Deep Bayesian Trust : A Dominant Strategy and Fair Reward Mechanism for Crowdsourcing. CoRR abs/1804.05560 (2018) - [i18]Jun Lu, Wei Ma, Boi Faltings:
CompNet: Neural networks growing via the compact network morphism. CoRR abs/1804.10316 (2018) - [i17]Fei Mi, Boi Faltings:
Context Tree for Adaptive Session-based Recommendation. CoRR abs/1806.03733 (2018) - [i16]Dimitris Chatzopoulos, Sujit Gujar, Boi Faltings, Pan Hui:
Privacy Preserving and Cost Optimal Mobile Crowdsensing using Smart Contracts on Blockchain. CoRR abs/1808.04056 (2018) - [i15]Naman Goel, Boi Faltings:
Crowdsourcing with Fairness, Diversity and Budget Constraints. CoRR abs/1810.13314 (2018) - 2017
- [b1]Boi Faltings, Goran Radanovic:
Game Theory for Data Science: Eliciting Truthful Information. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2017 - [j51]Boi Faltings, Goran Radanovic:
Mechanismen zur Beschaffung korrekter Daten. Inform. Spektrum 40(1): 64-74 (2017) - [j50]Brammert Ottens, Christos Dimitrakakis, Boi Faltings:
DUCT: An Upper Confidence Bound Approach to Distributed Constraint Optimization Problems. ACM Trans. Intell. Syst. Technol. 8(5): 69:1-69:27 (2017) - [c215]Fei Mi, Boi Faltings:
Adaptive Sequential Recommendation for Discussion Forums on MOOCs using Context Trees. EDM 2017 - [i14]Boi Faltings, Radu Jurca, Goran Radanovic:
Peer Truth Serum: Incentives for Crowdsourcing Measurements and Opinions. CoRR abs/1704.05269 (2017) - [i13]Chaitanya K. Joshi, Fei Mi, Boi Faltings:
Personalization in Goal-Oriented Dialog. CoRR abs/1706.07503 (2017) - [i12]Dimitris Chatzopoulos, Sujit Gujar, Boi Faltings, Pan Hui:
LocalCoin: An Ad-hoc Payment Scheme for Areas with High Connectivity. CoRR abs/1708.08086 (2017) - [i11]Goran Radanovic, Boi Faltings:
Partial Truthfulness in Minimal Peer Prediction Mechanisms with Limited Knowledge. CoRR abs/1711.06614 (2017) - [i10]Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings:
Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints. CoRR abs/1711.06740 (2017) - 2016
- [j49]Goran Radanovic, Boi Faltings, Radu Jurca:
Incentives for Effort in Crowdsourcing Using the Peer Truth Serum. ACM Trans. Intell. Syst. Technol. 7(4): 48:1-48:28 (2016) - [c214]Sujit Gujar, Boi Faltings:
Auction Based Mechanisms for Dynamic Task Assignments in Expert Crowdsourcing. AMEC/TADA 2016: 50-65 - [c213]Goran Radanovic, Boi Faltings:
Limiting the Influence of Low Quality Information in Community Sensing. AAMAS 2016: 873-881 - [c212]Sujit Gujar, Boi Faltings:
Online Auctions for Dynamic Assignment: Theory and Empirical Evaluation. ECAI 2016: 1035-1043 - [c211]Goran Radanovic, Boi Faltings:
Learning to Scale Payments in Crowdsourcing with PropeRBoost. HCOMP 2016: 179-188 - [c210]Fei Mi, Boi Faltings:
Adaptive Sequential Recommendation Using Context Trees. IJCAI 2016: 4018-4019 - [c209]Dimitris Chatzopoulos, Sujit Gujar, Boi Faltings, Pan Hui:
LocalCoin: An ad-hoc payment scheme for areas with high connectivity: poster. MobiHoc 2016: 365-366 - 2015
- [c208]Goran Radanovic, Boi Faltings:
Incentives for Subjective Evaluations with Private Beliefs. AAAI 2015: 1014-1020 - [c207]Goran Radanovic, Boi Faltings:
Incentive Schemes for Participatory Sensing. AAMAS 2015: 1081-1089 - [c206]Goran Radanovic, Boi Faltings:
Incentivizing truthful responses with the logarithmic peer truth serum. UbiComp/ISWC Adjunct 2015: 1349-1354 - [c205]Claudiu Cristian Musat, Boi Faltings:
Personalizing Product Rankings Using Collaborative Filtering on Opinion-Derived Topic Profiles. IJCAI 2015: 830-836 - [c204]Andrii Maksai, Florent Garcin, Boi Faltings:
Predicting Online Performance of News Recommender Systems Through Richer Evaluation Metrics. RecSys 2015: 179-186 - 2014
- [j48]Ludek Cigler, Boi Faltings:
Symmetric Subgame-Perfect Equilibria in Resource Allocation. J. Artif. Intell. Res. 49: 323-361 (2014) - [j47]