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22 records from EconBiz based on author Name
1. Towards data auctions with externalities
Agarwal, Anish; Dahleh, Munther A.; Horel, Thibaut; Rui, Maryann;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability:
Link 2. Automation of strategic data prioritization in system model calibration : sensor placement
Li, Tianyi; Dahleh, Munther A.;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
3. Contingent linear financial networks
Jiang, Bomin; Rigobón, Roberto; Dahleh, Munther A.;2024
Type: Aufsatz im Buch; Book section;
Availability:
Link 4. Towards Data Auctions with Externalities
abstractThe design of data markets has gained importance as firms increasingly use machine learning models fueled by externally acquired training data. A key consideration is the externalities firms face when data, though inherently freely replicable, is allocated to competing firms. In this setting, we demonstrate that a data seller’s optimal revenue increases as firms can pay to prevent allocations to others. To do so, we first reduce the combinatorial problem of allocating and pricing multiple datasets to the auction of a single digital good by modeling utility for data through the increase in prediction accuracy it provides. We then derive welfare and revenue maximizing mechanisms, highlighting how the form of firms’ private information– whether the externalities one exerts on others is known, or vice-versa– affects the resulting structures. In all cases, the optimal allocation rule is a single threshold per firm, where either all data is allocated or none is
Agarwal, Anish; Dahleh, Munther A.; Horel, Thibaut; Rui, Maryann;2023
Availability: Link Link
5. Contingent Linear Financial Networks
abstractIn this paper, we develop a methodology to estimate hidden linear networks when only an aggregate outcome is observed. The aggregate observable variable is a linear combination of the different networks and it is assumed that each network corresponds to the transmission mechanism of different shocks. We implement the methodology to estimate financial networks among US financial institutions. Credit Default Swap rates are the observable variable and we show that more than one network is needed to understand the dynamic behavior exhibited in the data
Jiang, Bomin; Rigobón, Roberto; Dahleh, Munther A.;2020
Availability: Link Link
Citations: 1 (based on OpenCitations)
6. Contingent linear financial networks
Jiang, Bomin; Rigobón, Roberto; Dahleh, Munther A.;2020
Type: Graue Literatur; Non-commercial literature; Arbeitspapier; Working Paper;
Availability: Link
7. Contingent Linear Financial Networks
abstractIn this paper, we develop a methodology to estimate hidden linear networks when only an aggregate outcome is observed. The aggregate observable variable is a linear mixture of the different networks and it is assumed that each network corresponds to the transmission mechanism of different shocks. We implement the methodology to estimate financial networks among US financial institutions. Credit Default Swap rates are the observable variable and we show that more than one network is needed to understand the dynamic behavior exhibited in the data
Jiang, Bomin; Rigobón, Roberto; Dahleh, Munther A.;2022
Availability: Link
8. Automation of Strategic Data Prioritization in System Model Calibration : Sensor Placement
abstractModel calibration is challenging for large-scale system models with a great number of variables. Existing approaches to partitioning of system models and prioritizing data acquisition rely on heuristics rather than formal treatments. The sensor placement problem on physical dynamic systems points to a promising avenue for formalizing strategic data prioritization and partial model calibration, which addresses the following question on system models: with the model at hand and a pre-existing data availability on certain model variables, what are the (next) k model variables that would bring the largest utility to model calibration, once their data are acquired? In this study, we formalize this problem as combinatorial optimization and adapt two solutions for physical systems to system models in social sciences: the information-entropy method and the miss-probability method, from physical systems to system models in social sciences. Then, based on the idea of Data Availability Partition, we develop a third method. The new method can be understood from the entropy perspective and is embedded in the theoretical framework for the evaluation of side information. Our solution applies to system models of different topologies: analytical results of optimal placement are derived for binary/multi-ary trees; for general tree structures, the algorithm to determine optimal placement is developed, whose complexity is upper-bounded by O(nlog_2(n)) for an n-variable model; for arbitrary model topologies with the presence of loops, sequential-optimal and simulated-annealing solvers are formulated. Three methods are compared on a transparent validating model structure; our method outperforms the two translated methods, yielding practical and robust solutions across different usage scenarios. Its stability in decision recommendation is coupled with the method's sufficient accommodation of the conditional nature of the placement problem. Application on a multi-compartment system model further showcases the toolkit's practical utility
Li, Tianyi; Dahleh, Munther A.;2022
Availability: Link Link
9. Selling information in competitive environments
Bonatti, Alessandro; Dahleh, Munther A.; Horel, Thibaut; Nouripour, Amir;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability:
Link 10. Coordination with local information
Dahleh, Munther A.; Tahbaz-Salehi, Alireza; Tsitsiklis, John N.; Zoumpoulis, Spyros I.;2016
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link
Citations: 6 (based on OpenCitations)
