Publications (Show abstracts)

2018

  • Any-k: Anytime top-k tree pattern retrieval in labeled graphs
    Xiaofeng Yang, Deepak Ajwani, Wolfgang Gatterbauer, Patrick K. Nicholson, Mirek Riedewald, Alessandra Sala
    WWW, pp. 489-498, 2018.
    [ACM], [Full version], [Full arXiv version], [gs], [bib]
    Many problems in areas as diverse as recommendation systems, social network analysis, semantic search, and distributed root cause analysis can be modeled as pattern search on labeled graphs (also called "heterogeneous information networks" or HINs). Given a large graph and a query pattern with node and edge label constraints, a fundamental challenge is to find the top-k matches according to a ranking function over edge and node weights. For users, it is difficult to select value k. We therefore propose the novel notion of an any-k ranking algorithm: for a given time budget, return as many of the top-ranked results as possible. Then, given additional time, produce the next lower-ranked results quickly as well. It can be stopped anytime, but may have to continue until all results are returned. This paper focuses on acyclic patterns over arbitrary labeled graphs. We are interested in practical algorithms that effectively exploit (1) properties of heterogeneous networks, in particular selective constraints on labels, and (2) that the users often explore only a fraction of the top-ranked results. Our solution, KARPET, carefully integrates aggressive pruning that leverages the acyclic nature of the query, and incremental guided search. It enables us to prove strong non-trivial time and space guarantees, which is generally considered very hard for this type of graph search problem. Through experimental studies we show that KARPET achieves running times in the order of milliseconds for tree patterns on large networks with millions of nodes and edges.
  • Dissociation-based oblivious bounds for weighted model counting
    Li Chou, Wolfgang Gatterbauer, Vibhav Gogate
    UAI, 2018.
    [UAI], [preprint], [gs], [bib]
    Generalizes the oblivious bounds from TODS 2014 from monotone to non-monotone Boolean functions
    We consider the weighted model counting task which includes important tasks in graphical models, such as computing the partition function and probability of evidence as special cases. We propose a novel partition-based bounding algorithm that exploits logical structure and gives rise to a set of inequalities from which upper (or lower) bounds can be derived efficiently. The bounds come with optimality guarantees under certain conditions and are oblivious in that they require only limited observations of the structure and parameters of the problem. We experimentally compare our bounds with the mini-bucket scheme (which is also oblivious) and show that our new bounds are often superior and never worse on a wide variety of benchmark networks.
  • A General framework for anytime approximation in probabilistic databases.
    Maarten Van den Heuvel, Floris Geerts, Wolfgang Gatterbauer, Martin Theobald
    StarAI (IJCAI workshop), 2018 (Short position paper).
    [arXiv], [preprint], [gs]
    Anytime approximation algorithms that compute the probabilities of queries over probabilistic databases can be of great use to statistical learning tasks. Those approaches have been based so far on either (i) sampling or (ii) branch-and-bound with model-based bounds. We present here a more general branch-and-bound framework that extends the possible bounds by using "dissociation," which yields tighter bounds.
  • PISTIS: A conflict of interest declaration and detection system for peer review management
    Siyuan Wu, Leong Hou U, Sourav S. Bhowmick, Wolfgang Gatterbauer
    SIGMOD, pp. 1713-1716, 2018 (System demonstration).
    [ACM], [preprint], [bib]
    Detecting conflicts of interest (COIs) is key for guaranteeing the fairness of a peer-review process. In many conference management systems, the COIs of authors and reviewers are self-declared, and the declaration process is time consuming and potentially incomplete. To address this problem, we demonstrate a novel interactive system called PISTIS that assists the declaration process in a semi-automatic manner. Apart from keyword search and simple filtering, our system provides an interactive graphical interface that helps users explore potential COIs based on the heterogenous data sources. To simply the process of declaration, we also recommend latent COIs using a supervised ranking model that can be iteratively refined from the data collected from past declarations. We believe that PISTIS can be useful as an assistant tool in many real world conference management systems
  • Algorithms for automatic ranking of participants and tasks in an anonymized contest
    Yang Jiao, R. Ravi, Wolfgang Gatterbauer
    Theoretical Computer Science, Elsevier, 2018 (Special Issue on WALCOM 2017, in press).
    [Elsevier], [preprint], [arXiv old]
    Extended version of WALCOM 2017
    We introduce a new set of problems based on the Chain Editing problem. In our version of Chain Editing, we are given a set of participants and a set of tasks that every participant attempts. For each participant-task pair, we know whether the participant has succeeded at the task or not. We assume that participants vary in their ability to solve tasks, and that tasks vary in their difficulty to be solved. In an ideal world, stronger participants should succeed at a superset of tasks that weaker participants succeed at. Similarly, easier tasks should be completed successfully by a superset of participants who succeed at harder tasks. In reality, it can happen that a stronger participant fails at a task that a weaker participants succeeds at. Our goal is to find a perfect nesting of the participant-task relations by flipping a minimum number of participant-task relations, implying such a "nearest perfect ordering" to be the one that is closest to the truth of participant strengths and task difficulties. Many variants of the problem are known to be NP-hard.
  • Beta Probabilistic Databases: A scalable approach to belief updating and parameter learning
    Niccolò Meneghetti, Oliver Kennedy, Wolfgang Gatterbauer
    TODS, 2018 (Special Issue on SIGMOD 2017, to appear).
    Extended version of SIGMOD 2017

2017

  • Beta probabilistic databases: A scalable approach to belief updating and parameter learning
    Niccolo Meneghetti, Oliver Kennedy, Wolfgang Gatterbauer
    SIGMOD, pp. 573-586, 2017.
    [ACM], [preprint], [gs], [bib]
    Invited to the Special Issue of TODS on "best of SIGMOD 2017"
    Tuple-independent probabilistic databases (TI-PDBs) handle uncertainty by annotating each tuple with a probability parameter; when the user submits a query, the database derives the marginal probabilities of each output-tuple, assuming input-tuples are statistically independent. While query processing in TI-PDBs has been studied extensively, limited research has been dedicated to the problems of updating or deriving the parameters from observations of query results. Addressing this problem is the main focus of this paper. We introduce Beta Probabilistic Databases (B-PDBs), a generalization of TI-PDBs designed to support both (i) belief updating and (ii) parameter learning in a principled and scalable way. The key idea of B-PDBs is to treat each parameter as a latent, Beta-distributed random variable. We show how this simple expedient enables both belief updating and parameter learning in a principled way, without imposing any burden on regular query processing. We use this model to provide the following key contributions: (i) we show how to scalably compute the posterior densities of the parameters given new evidence; (ii) we study the complexity of performing Bayesian belief updates, devising efficient algorithms for tractable classes of queries; (iii) we propose a soft-EM algorithm for computing maximum-likelihood estimates of the parameters; (iv) we show how to embed the proposed algorithms into a standard relational engine; (v) we support our conclusions with extensive experimental results.
  • The linearization of belief propagation on pairwise Markov Random Fields
    Wolfgang Gatterbauer
    AAAI, pp. 3747-3753, 2017.
    [paper], [Full arXiv version], [bib]
    Generalizes the linearization from VLDB 2015 to arbitrary pairwise MRFs
    Belief Propagation (BP) is a widely used approximation for exact probabilistic inference in graphical models, such as Markov Random Fields (MRFs). In graphs with cycles, however, no exact convergence guarantees for BP are known, in general. For the case when all edges in the MRF carry the same symmetric, doubly stochastic potential, recent works have proposed to approximate BP by linearizing the update equations around default values, which was shown to work well for the problem of node classification. The present paper generalizes all prior work and derives an approach that approximates loopy BP on any pairwise MRF with the problem of solving a linear equation system. This approach combines exact convergence guarantees and a fast matrix implementation with the ability to model heterogenous networks. Experiments on synthetic graphs with planted edge potentials show that the linearization has comparable labeling accuracy as BP for graphs with weak potentials, while speeding-up inference by orders of magnitude.
  • Conflict of interest declaration and detection system in heterogeneous networks
    Siyuan Wu, Leong Hou U, Sourav S Bhowmick, Wolfgang Gatterbauer.
    CIKM, pp. 2383-2386, 2017 (Short paper).
    [ACM], [preprint], [gs] [bib]
    Peer review is the most critical process in evaluating an article to be accepted for publication in an academic venue. When assigning a reviewer to evaluate an article, the assignment should be aware of conflicts of interest (COIs) such that the reviews are fair to everyone. However, existing conference management systems simply ask reviewers and authors to declare their explicit COIs through a plain search user interface guided by some simple conflict rules. We argue that such declaration system is not enough to discover all latent COI cases. In this work, we study a graphical declaration system that visualizes the relationships of authors and reviewers based on a heterogeneous co-authorship network. With the help of the declarations, we attempt to detect the latent COIs automatically based on the meta-paths of a heterogeneous network.
  • Algorithms for automatic ranking of participants and tasks in an anonymized contest
    Yang Jiao, R. Ravi, Wolfgang Gatterbauer
    WALCOM, pp 335-346, 2017.
    [Springer], [arXiv], [bib]
    Invited to the Special Issue of Elsevier TCS on WALCOM 2017
    We consider the weighted model counting task which includes important tasks in graphical models, such as computing the partition function and probability of evidence as special cases. We propose a novel partition-based bounding algorithm that exploits logical structure and gives rise to a set of inequalities from which upper (or lower) bounds can be derived efficiently. The bounds come with optimality guarantees under certain conditions and are oblivious in that they require only limited observations of the structure and parameters of the problem. We experimentally compare our bounds with the mini-bucket scheme (which is also oblivious) and show that our new bounds are often superior and never worse on a wide variety of benchmark networks.
  • Dissociation and propagation for approximate lifted inference with standard relational database management systems
    Wolfgang Gatterbauer, Dan Suciu
    VLDBJ (Special Issue of VLDB Journal on VLDB 2015). pp. 5-30, 2016.
    selection [Springer], [Full arXiv version]
    Project page: Propagation
    Extends VLDB 2015 with all proofs and shows how the approch generalizes the idea of "graph propagation" to propagation on hypergraphs
    This paper proposes an approach to uncertain query evaluation by which every query is evaluated entirely in the database engine by evaluating a fixed number of query plans, each providing an upper bound on the true probability, then taking their minimum. We provide an algorithm that takes into account important schema information to enumerate only the minimal necessary plans among all possible plans. Importantly, this algorithm is a strict generalization of all known PTIME self-join-free conjunctive queries: A query is in PTIME if and only if our algorithm returns one single plan. Furthermore, our approach is a generalization of a family of efficient ranking functions from graphs to hypergraphs. We also note that the techniques developed in this paper apply immediately to lifted inference from statistical relational models since lifted inference corresponds to PTIME plans in probabilistic databases.

2016

  • Semi-supervised learning with heterophily
    Wolfgang Gatterbauer
    arXiv:1412.3100.
    [working paper]
    Project page: SSL-H
    We propose a novel linear semi-supervised learning formulation that is derived from a solid probabilistic framework: belief propagation. We show that our formulation generalizes a number of label propagation algorithms described in the literature by allowing them to propagate generalized assumptions about influences between classes of neighboring nodes. We call this formulation Semi-Supervised Learning with Heterophily (SSL-H). We also show how the modularization matrix can be learned from observed data with a simple convex optimization framework that is inspired by locally linear embedding. We call this approach Linear Heterophily Estimation (LHE). Experiments on synthetic data show that both approaches combined can learn heterophily of agraph with 1M nodes and 10M edges in under 1min.

2015

  • The complexity of resilience and responsibility for self-join-free conjunctive queries
    Cibele Freire, Wolfgang Gatterbauer, Neil Immerman, Alexandra Meliou
    PVLDB 9(3):180-191, 2015.
    selection [VLDB], [full arXiv version], [bib]
    Project page: Causality
    Several research thrusts in the area of data management have focused on understanding how changes in the data affect the output of a view or standing query. Example applications are explaining query results, propagating updates through views, and anonymizing datasets. These applications usually rely on understanding how interventions in a database impact the output of a query. An important aspect of this analysis is the problem of deleting a minimum number of tuples from the input tables to make a given Boolean query false. We refer to this problem as "the resilience of a query" and show its connections to the well-studied problems of deletion propagation and causal responsibility. In this paper, we study the complexity of resilience for self-join-free conjunctive queries, and also make several contributions to previous known results for the problems of deletion propagation with source side-effects and causal responsibility: (1) We define the notion of resilience and provide a complete dichotomy for the class of self-join-free conjunctive queries with arbitrary functional dependencies; this dichotomy also extends and generalizes previous tractability results on deletion propagation with source side-effects. (2) We formalize the connection between resilience and causal responsibility, and show that resilience has a larger class of tractable queries than responsibility. (3) We identify a mistake in a previous dichotomy for the problem of causal responsibility and offer a revised characterization based on new, simpler, and more intuitive notions. (4) Finally, we extend the dichotomy for causal responsibility in two ways: (a) we treat cases where the input tables contain functional dependencies, and (b) we compute responsibility for a set of tuples specified via wildcards.
  • Linearized and single-pass belief propagation
    Wolfgang Gatterbauer, Stephan Günnemann, Danai Koutra, Christos Faloutsos
    PVLDB 8(5):581-592, 2015.
    selection [VLDB], [Full arXiv version], [slides (2MB)], [narrated slides (32MB)], [video (21min)], [Python code], [SQL code], [bib]
    Project page: SSL-H
    How can we tell when accounts are fake or real in a social network? And how can we tell which accounts belong to liberal, conservative or centrist users? Often, we can answer such questions and label nodes in a network based on the labels of their neighbors and appropriate assumptions of homophily ("birds of a feather flock together") or heterophily ("opposites attract"). One of the most widely used methods for this kind of inference is Belief Propagation (BP) which iteratively propagates the information from a few nodes with explicit labels throughout a network until convergence. A well-known problem with BP, however, is that there are no known exact guarantees of convergence in graphs with loops. This paper introduces Linearized Belief Propagation (LinBP), a linearization of BP that allows a closed-form solution via intuitive matrix equations and, thus, comes with exact convergence guarantees. It handles homophily, heterophily, and more general cases that arise in multi-class settings. Plus, it allows a compact implementation in SQL. The paper also introduces Single-pass Belief Propagation (SBP), a localized (or "myopic") version of LinBP that propagates information across every edge at most once and for which the final class assignments depend only on the nearest labeled neighbors. In addition, SBP allows fast incremental updates in dynamic networks. Our runtime experiments show that LinBP and SBP are orders of magnitude faster than standard BP, while leading to almost identical node labels.
  • Approximate lifted inference with probabilistic databases
    Wolfgang Gatterbauer, Dan Suciu
    PVLDB 8(5):629-640, 2015.
    selection [VLDB], [arXiv version], [slides (4MB)], [bib]
    Project page: Propagation
    Invited to the Special Issue of VLDB Journal on VLDB 2015
    This paper proposes a new approach for approximate evaluation of #P-hard queries with probabilistic databases. In our approach, every query is evaluated entirely in the database engine by evaluating a fixed number of query plans, each providing an upper bound on the true probability, then taking their minimum. We provide an algorithm that takes into account important schema information to enumerate only the minimal necessary plans among all possible plans. Importantly, this algorithm is a strict generalization of all known results of PTIME self-join-free conjunctive queries: A query is safe if and only if our algorithm returns one single plan. We also apply three relational query optimization techniques to evaluate all minimal safe plans very fast. We give a detailed experimental evaluation of our approach and, in the process, provide a new way of thinking about the value of probabilistic methods over non-probabilistic methods for ranking query answers.
  • Fault-Tolerant Entity Resolution with the Crowd
    Anja Gruenheid, Besmira Nushi, Tim Kraska, Wolfgang Gatterbauer, Donald Kossmann
    arXiv:1512.00537.
    [arXiv]

2014

  • Oblivious bounds on the probability of Boolean functions
    Wolfgang Gatterbauer, Dan Suciu
    ACM TODS, vol. 39, no. 1, pp. 191-208, 2014.
    selection [ACM], [preprint], [arXiv], [SQL code], [Java code for GT] [bib],
    Prior superseded working paper "Optimal Upper and Lower Bounds for Boolean Expressions by Dissociation": arXiv:1105.2813
    Project page: Propagation
    This paper develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an exact characterization of optimal oblivious bounds, i.e. when the new probabilities are chosen independent of the probabilities of all other variables. Our motivation comes from the weighted model counting problem (or, equivalently, the problem of computing the probability of a Boolean function), which is #P-hard in general. By performing several dissociations, one can transform a Boolean formula whose probability is difficult to compute, into one whose probability is easy to compute, and which is guaranteed to provide an upper or lower bound on the probability of the original formula by choosing appropriate probabilities for the dissociated variables. Our new bounds shed light on the connection between previous relaxation-based and model-based approximations and unify them as concrete choices in a larger design space. We also show how our theory allows a standard relational database management system (DBMS) to both upper and lower bound hard probabilistic queries in guaranteed polynomial time.

2013

  • Counterexamples to commonly held assumptions on unit commitment and market power assessment
    Wolfgang Gatterbauer, Marija Ilic
    Chapter 10 of: Engineering IT-Enabled Sustainable Electricity Services, Marija Ilic, Le Xie, Qizing Liu (Eds.), Springer, 2013.
    [chapter]
    Within the context of the ongoing deregulation of the electricity industry, we disprove in the first part the commonly stated assumption that, in theory and under the condition of perfect information, decentralized and centralized unit commitment would lead to the same power quantities traded and, hence, to the same optimal social welfare. We show that, even in the absence of any uncertainties, independent optimization of the individual performance objectives by the decentralized market participants can actually lead to lower efficiency than centralized minimization of total operating cost. This result concerns short-term supply optimization for a given demand, and does not consider long-term investment issues. In the second part, we take the position of an individual market participant in a deregulated electricity market. We investigate the task of optimally self-scheduling generators to maximize profits by using stochastic dynamic programming. With the help of actual price forecast data from the ISO New England electricity wholesale market, we demonstrate the improvements that result from modeling the forecast price errors assuming a Cauchy error distribution instead of the commonly used Normal distribution.

2012

  • Querying provenance for ranking and recommending
    Zachary Ives, Andreas Haeberlen, Tao Feng, Wolfgang Gatterbauer.
    TaPP 2012.
    [paper]

2011

  • Default-all is dangerous!
    Wolfgang Gatterbauer, Alexandra Meliou, Dan Suciu
    TaPP 2011.
    selection [paper], [paper (arXiv:1105.4395)], [slides], [slides], [bib]
    Project pages: BeliefDB, Causality
    This paper shows that the "default-all propagation" scheme for database annotations can have some problematic semantic consequences. We propose an alternative "minimum-propagation" provenance that fixes the issue and that comes with several desirable properties.
  • Rules of thumb for information acquisition from large and redundant data
    Wolfgang Gatterbauer
    ECIR 2011, pp. 479-490.
    selection [paper], [slides], [slides], [bib],
    Full 40 page version with all proofs (arXiv:1012.3502): [paper (arXiv:1012.3502)], [bib], (Version Dec 2010)
    Project page: Unique recall
    Assume you crawl 20% of the Web. Are you able to learn 80% of the available information? This paper develops an analytic model (and uses generally accepted assumptions of power laws distributions in data) to show that we can expect to learn less then 40% of the Web's content, hence the 80-20 rules does not hold. The paper further describes a new family of power law distribution which remains invariant under sampling, i.e. randomly sampling from this distribution will lead again to the original distribution in the sample.
  • QueryViz: Helping users understand SQL queries and their patterns
    Jonathan Danaparamita, Wolfgang Gatterbauer
    EDBT 2011, pp. 558-561. (System demonstration)
    selection [demonstration paper], [demonstration paper (ACM version)], [bib]
    Project page: QueryViz
  • Tracing data errors with view-conditioned causality
    Alexandra Meliou, Wolfgang Gatterbauer, Suman Nath, Dan Suciu
    SIGMOD 2011, pp. 505-516.
    selection [paper], [paper (ACM version)], [bib]
    Project page: Causality
    This paper shows how causal reasoning can be used for post-factum data cleaning, where errors are detected after data has been transformed (e.g. by a query) and which need to be corrected in the original input data. We achieve this with a novel way for translating the problem into a SAT and a weighted MAX-SAT problem, and then using very effective existing tools.
  • Databases will visualize queries too
    Wolfgang Gatterbauer
    PVLDB 4(12):1498-1501, 2011. (VLDB challenges and visions track)
    [paper], [narrated slides (16MB)], [video (19min)], [bib]
    Project page: QueryViz
    This paper describes a human-query interaction pattern in which users re-use existing queries as templates to compose their own queries. This interaction mode is only made possible with new visualization tools which help users understand SQL patterns and the intent of existing SQL queries quickly. QueryViz is our new visualization approach.
  • Managing structured collections of community data
    Wolfgang Gatterbauer, Dan Suciu
    CIDR 2011, pp. 207-210. (Outrageous ideas and vision track)
    [vision paper], [slides], [slides], [bib]
    Project page: BeliefDB
  • Reverse data management
    Alexandra Meliou, Wolfgang Gatterbauer, Dan Suciu
    PVLDB 4(12):1490-1493, 2011. (VLDB challenges and visions track)
    [paper], [bib]
    Project page: Causality
  • Bringing provenance to its full potential using causal reasoning
    Alexandra Meliou, Wolfgang Gatterbauer, Dan Suciu
    TaPP 2011.
    [paper], [bib]
    Project page: Causality
  • Session-based browsing for better query reuse
    Nodira Khoussainova, Yongchul Kwon, Wei-Ting Liao, Magdalena Balazinska, Wolfgang Gatterbauer, Dan Suciu
    SSDBM 2011, pp. 583-585. (Poster)
    [poster paper]
    Full 10 page version (UW CSE TR 11-04-02): [technical report]
    Project page: CQMS

2010

2009

2007

  • Towards domain-independent information extraction from web tables
    Wolfgang Gatterbauer, Paul Bohunsky, Marcus Herzog, Bernhard Kr�pl, Bernhard Pollak
    WWW 2007, pp. 71-80.
    selection [paper], [paper (ACM version)], [bib], [Citations],
    Copy of former Project page: VENTex
    Patent 8,719,291
  • Creating permanent test collections of web pages for information extraction research
    Bernhard Pollak, Wolfgang Gatterbauer
    SOFSEM 2007, Volume II, pp. 103-115.
    [paper], [slides], [poster], [bib]
    Project pages: WebPageDump, VENTex
    WebPageDump is a Firefox extension which allows you to save local copies of pages from the Web. It sounds simple, but it's not. The standard "Save page as" function of web browsers fails with most dynamic web pages and this shortcoming was a serious problem for our research. Comes the birth of WebPageDump. We hope you find it useful too.

2006

2005

  • Using visual cues for extraction of tabular data from arbitrary HTML documents
    Bernhard Kr�pl, Marcus Herzog, Wolfgang Gatterbauer.
    WWW 2005, pp. 1000-1001. (Poster)
    [poster paper], [bib]
  • Web information extraction using eupeptic data in Web tables
    Wolfgang Gatterbauer, Bernhard Kr�pl, Wolfgang Holzinger, Marcus Herzog.
    RAWS 2005 (1st International Workshop on Representation and Analysis of Web Space), pp. 41-48.
    [paper], [bib]

2002 (Electrical Engineering)

  • Counterexamples to commonly held assumptions on unit commitment and market power assessment
    Wolfgang Gatterbauer, Marija Ilic
    NAPS 2002 (34th Annual North American Power Symposium), pp. 219-225.
    [paper], [slides], [bib]
  • Interdependencies of electricity market characteristics and bidding strategies of power producers
    Wolfgang Gatterbauer
    Master's thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, May 2002.
    [thesis], [bib]
    Within the context of the ongoing deregulation of the electricity industry, we disprove in the first part the commonly stated assumption that, in theory and under the condition of perfect information, decentralized and centralized unit commitment would lead to the same power quantities traded and, hence, to the same optimal social welfare. We show that, even in the absence of any uncertainties, independent optimization of the individual performance objectives by the decentralized market participants can actually lead to lower efficiency than centralized minimization of total operating cost. This result concerns short-term supply optimization for a given demand, and does not consider long-term investment issues.
          In the second part, we take the position of an individual market participant in a deregulated electricity market. We investigate the task of optimally self-scheduling generators to maximize profits by using stochastic dynamic programming. With the help of actual price forecast data from the ISO New England electricity wholesale market, we demonstrate the improvements that result from modeling the forecast price errors assuming a Cauchy error distribution instead of the commonly used Normal distribution.
          Finally, by taking statistic uncertainties and inter-temporal interdependencies into account, we show in the third part that a generator owner's optimum bid sequence for a centralized auction market is generally above marginal cost. In contrast to current literature, this is true even where absolutely no abuse of market power is involved. We conclude that marginal production costs cannot be used by themselves as baseline for the assessment of market power in electricity markets.

2000 (Mechanical Engineering)

  • Combining the Graz Cycle with coal and heavy oil gasification for industrial power stations
    Original title in German: Der Graz Cycle für Industriekraftwerke gefeuert mit Brenngasen aus Kohle- und Schwerölvergasung
    Herbert Jericha, Armin Lukasser, Wolfgang Gatterbauer
    VDI-Berichte Nr. 1566, Gas Turbines for Combined Cycles, pp. 177-185, Essen, Germany, September 2000.
    [paper], [bib]
    Project page: Graz Cycle