G. Katz, P. Piantanida, and M. Debbah, Distributed Binary Detection with Lossy Data Compression, IEEE Transactions on Information Theory
DOI : 10.1109/TIT.2017.2688348

URL : https://hal.archives-ouvertes.fr/hal-01322313

G. Katz, P. Piantanida, and M. Debbah, Collaborative Distributed Hypothesis Testing " , (submitted to) The Annals of Applied Probability. (Available online, p.160

G. Katz, P. Piantanida, R. Couillet, and M. Debbah, Joint estimation and detection against independence, 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2014.
DOI : 10.1109/ALLERTON.2014.7028594

URL : https://hal.archives-ouvertes.fr/hal-01098853

G. Katz, P. Piantanida, R. Couillet, and M. Debbah, On the necessity of binning for the distributed hypothesis testing problem, 2015 IEEE International Symposium on Information Theory (ISIT), 2015.
DOI : 10.1109/ISIT.2015.7282966

URL : https://hal.archives-ouvertes.fr/hal-01242524

G. Katz, P. Piantanida, and M. Debbah, Collaborative distributed hypothesis testing with general hypotheses, 2016 IEEE International Symposium on Information Theory (ISIT), 2016.
DOI : 10.1109/ISIT.2016.7541590

URL : https://hal.archives-ouvertes.fr/hal-01436846

G. Katz, P. Piantanida, and M. Debbah, A new approach to distributed hypothesis testing, 2016 50th Asilomar Conference on Signals, Systems and Computers
DOI : 10.1109/ACSSC.2016.7869599

URL : https://hal.archives-ouvertes.fr/hal-01436813

E. Lehmann and J. Romano, Testing Statistical Hypotheses, ser, 2005.

T. M. Cover and J. A. Thomas, Elements of information theory, 1991.

V. Y. Tan, Stein's lemma, " in Information Theory for Communication Systems, EE5139R Lecture 12 Available: https, 2015.

R. Tenney and N. R. Sandell, Detection with distributed sensors Aerospace and Electronic Systems, IEEE Transactions on, issue.4, pp.501-510, 1981.
DOI : 10.1109/cdc.1980.271833

T. Han and S. Amari, Statistical inference under multiterminal data compression Information Theory, IEEE Transactions on, vol.44, issue.6, pp.2300-2324, 1998.

A. Wald, Sequential Tests of Statistical Hypotheses, The Annals of Mathematical Statistics, vol.16, issue.2, pp.117-186, 1945.
DOI : 10.1214/aoms/1177731118

A. Wald and J. Wolfowitz, Optimum Character of the Sequential Probability Ratio Test, The Annals of Mathematical Statistics, vol.19, issue.3, pp.326-339, 1948.
DOI : 10.1214/aoms/1177730197

R. Ahlswede and I. Csiszar, Hypothesis testing with communication constraints Information Theory, IEEE Transactions on, vol.32, issue.4, pp.533-542, 1986.
DOI : 10.1109/tit.1986.1057194

URL : https://pub.uni-bielefeld.de/download/1780427/2312909

T. Han, Hypothesis testing with multiterminal data compression, IEEE Transactions on Information Theory, vol.33, issue.6, pp.759-772, 1987.
DOI : 10.1109/TIT.1987.1057383

T. Berger, Rate-Distortion Theory, 1971.
DOI : 10.1002/0471219282.eot142

M. Bloch, J. Barros, M. R. Rodrigues, and S. W. Mclaughlin, Wireless Information-Theoretic Security, IEEE Transactions on Information Theory, vol.54, issue.6, pp.2515-2534, 2008.
DOI : 10.1109/TIT.2008.921908

U. M. Maurer, Protocols for Secret Key Agreement by Public Discussion Based on Common Information, Annual International Cryptology Conference, pp.461-470, 1992.
DOI : 10.1007/3-540-48071-4_32

C. H. Bennett, G. Brassard, and J. Robert, Privacy Amplification by Public Discussion, SIAM Journal on Computing, vol.17, issue.2, pp.210-229, 1988.
DOI : 10.1137/0217014

W. Diffie and M. Hellman, New directions in cryptography Information Theory, IEEE Transactions on, vol.22, issue.6, pp.644-654, 1976.
DOI : 10.1109/tit.1976.1055638

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.9720

Y. Lin, D. Varodayan, and B. Girod, Image Authentication Using Distributed Source Coding, IEEE Transactions on Image Processing, vol.21, issue.1, pp.273-283, 2012.
DOI : 10.1109/TIP.2011.2157515

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.261.3534

C. Lin and S. Chang, A robust image authentication method distinguishing jpeg compression from malicious manipulation Circuits and Systems for Video Technology, IEEE Transactions on, vol.11, issue.2, pp.153-168, 2001.

G. Chaojun, P. Jirutitijaroen, and M. Motani, Detecting false data injection attacks in ac state estimation Smart Grid, IEEE Transactions on, vol.6, issue.5, pp.2476-2483, 2015.
DOI : 10.1109/tsg.2015.2388545

A. Giani, E. Bitar, M. Garcia, M. Mcqueen, P. Khargonekar et al., Smart Grid Data Integrity Attacks, IEEE Transactions on Smart Grid, vol.4, issue.3, pp.1244-1253, 2013.
DOI : 10.1109/TSG.2013.2245155

Y. Xiang and Y. Kim, Interactive hypothesis testing with communication constraints, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp.1065-1072, 2012.
DOI : 10.1109/Allerton.2012.6483336

URL : http://circuit.ucsd.edu/~yhk/pdfs/allerton2012b.pdf

I. Csiszár, The method of types [information theory], IEEE Transactions on Information Theory, vol.44, issue.6, pp.2505-2523, 1998.
DOI : 10.1109/18.720546

L. Atzori, A. Iera, and G. Morabito, The Internet of Things: A survey, Computer Networks, vol.54, issue.15, pp.2787-2805, 2010.
DOI : 10.1016/j.comnet.2010.05.010

J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, Internet of Things (IoT): A vision, architectural elements, and future directions, Future Generation Computer Systems, vol.29, issue.7, pp.1645-1660, 2013.
DOI : 10.1016/j.future.2013.01.010

R. Khan, S. U. Khan, R. Zaheer, and S. Khan, Future Internet: The Internet of Things Architecture, Possible Applications and Key Challenges, 2012 10th International Conference on Frontiers of Information Technology, pp.257-260
DOI : 10.1109/FIT.2012.53

N. Li, M. Sun, Z. Bi, Z. Su, and C. Wang, A new methodology to support group decision-making for IoT-based emergency response systems, Information Systems Frontiers, vol.34, issue.4, pp.953-977, 2014.
DOI : 10.1007/s10796-013-9407-z

I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, Wireless sensor networks: a survey, Computer Networks, vol.38, issue.4, pp.393-422, 2002.
DOI : 10.1016/S1389-1286(01)00302-4

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.3866

P. Bonnet, J. Gehrke, and P. Seshadri, Querying the physical world, IEEE Personal Communications, vol.7, issue.5, pp.10-15, 2000.
DOI : 10.1109/98.878531

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.31.2204

A. Chandrakasan, R. Amirtharajah, S. Cho, J. Goodman, G. Konduri et al., Design considerations for distributed microsensor systems, Proceedings of the IEEE 1999 Custom Integrated Circuits Conference (Cat. No.99CH36327), pp.279-286, 1999.
DOI : 10.1109/CICC.1999.777291

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.26.7430

I. A. Essa, Ubiquitous sensing for smart and aware environments, IEEE Personal Communications, vol.7, issue.5, pp.47-49, 2000.
DOI : 10.1109/98.878538

T. M. Cover, Hypothesis Testing with Finite Statistics, The Annals of Mathematical Statistics, vol.40, issue.3, pp.828-835, 1969.
DOI : 10.1214/aoms/1177697590

M. E. Hellman and T. M. Cover, Learning with Finite Memory, The Annals of Mathematical Statistics, vol.41, issue.3, pp.765-782, 1970.
DOI : 10.1214/aoms/1177696958

URL : http://projecteuclid.org/download/pdf_1/euclid.aoms/1177696958

S. Yakowitz, Multiple Hypothesis Testing by Finite Memory Algorithms, The Annals of Statistics, vol.2, issue.2, pp.323-336, 1974.
DOI : 10.1214/aos/1176342666

URL : http://projecteuclid.org/download/pdf_1/euclid.aos/1176342666

J. Bucklew and P. Ney, Asymptotically Optimal Hypothesis Testing with Memory Constraints, The Annals of Statistics, vol.19, issue.2, pp.982-998, 1991.
DOI : 10.1214/aos/1176348132

URL : http://projecteuclid.org/download/pdf_1/euclid.aos/1176348132

T. Chiyonobu, Hypothesis Testing for Signal Detection Problem and Large Deviations, Nagoya Mathematical Journal, vol.39, pp.187-203, 2001.
DOI : 10.1017/S0027763000007868

R. Blahut, Hypothesis testing and information theory, IEEE Transactions on Information Theory, vol.20, issue.4, pp.405-417, 1974.
DOI : 10.1109/TIT.1974.1055254

R. Ahlswede and M. Burnashev, On Minimax Estimation in the Presence of Side Information About Remote Data, The Annals of Statistics, vol.18, issue.1, pp.141-171, 1990.
DOI : 10.1214/aos/1176347496

H. Shimokawa, T. Han, and S. Amari, Error bound of hypothesis testing with data compression, Proceedings of 1994 IEEE International Symposium on Information Theory, p.114, 1994.
DOI : 10.1109/ISIT.1994.394874

S. Rahman and A. Wagner, On the optimality of binning for distributed hypothesis testing Information Theory, IEEE Transactions on, vol.58, issue.10, pp.6282-6303, 2012.

A. Lapidoth and P. Narayan, Reliable communication under channel uncertainty Information Theory, IEEE Transactions on, vol.44, issue.6, pp.2148-2177, 1998.
DOI : 10.1109/18.720535

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.8368

H. Shalaby and A. Papamarcou, Multiterminal detection with zero-rate data compression Information Theory, IEEE Transactions on, vol.38, issue.2, pp.254-267, 1992.
DOI : 10.1109/18.119685

W. Zhao and L. Lai, Distributed testing with zero-rate compression, 2015 IEEE International Symposium on Information Theory (ISIT), pp.2792-2796, 2015.
DOI : 10.1109/ISIT.2015.7282965

Y. Steinberg and N. Merhav, On successive refinement for the wyner-ziv problem Information Theory, IEEE Transactions on, vol.50, issue.8, pp.1636-1654, 2004.

A. Wyner and J. Ziv, The rate-distortion function for source coding with side information at the decoder Information Theory, IEEE Transactions on, vol.22, issue.1, pp.1-10, 1976.

F. Fu and R. W. Yeung, On the rate-distortion region for multiple descriptions, IEEE Transactions on Information Theory, vol.48, issue.7, pp.2012-2021, 2002.

R. Timo, T. Chan, and A. Grant, Rate Distortion With Side-Information at Many Decoders, IEEE Transactions on Information Theory, vol.57, issue.8, pp.5240-5257, 2011.
DOI : 10.1109/TIT.2011.2158472

URL : http://arxiv.org/abs/0901.1705

C. Heegard and T. Berger, Rate distortion when side information may be absent, IEEE Transactions on Information Theory, vol.31, issue.6, pp.727-734, 1985.
DOI : 10.1109/TIT.1985.1057103

A. Kaspi, Rate-distortion function when side-information may be present at the decoder Information Theory, IEEE Transactions on, vol.40, issue.6, pp.2031-2034, 1994.
DOI : 10.1109/18.340475

C. Tian and J. Chen, Successive refinement for hypothesis testing and lossless onehelper problem Information Theory, IEEE Transactions on, vol.54, issue.10, pp.4666-4681, 2008.
DOI : 10.1109/tit.2008.928951

A. Kaspi, Two-way source coding with a fidelity criterion Information Theory, IEEE Transactions on, vol.31, issue.6, pp.735-740, 1985.

Y. Xiang and Y. Kim, Interactive hypothesis testing against independence, 2013 IEEE International Symposium on Information Theory, pp.2840-2844, 2013.
DOI : 10.1109/ISIT.2013.6620744

URL : http://circuit.ucsd.edu/~yhk/pdfs/isit2013c.pdf

S. Bayram and S. Gezici, Noise-enhanced M-ary hypothesis-testing in the minimax framework, 2009 3rd International Conference on Signal Processing and Communication Systems, pp.1-6, 2009.
DOI : 10.1109/ICSPCS.2009.5306400

M. Naghshvar and T. Javidi, Active M-ary sequential hypothesis testing, 2010 IEEE International Symposium on Information Theory, pp.1623-1627, 2010.
DOI : 10.1109/ISIT.2010.5513381

Z. B. Tang, K. R. Pattipati, and D. L. Kleinman, A distributed m-ary hypothesis testing problem with correlated observations, Decision and Control Proceedings of the 28th IEEE Conference on, pp.562-568, 1989.

X. Zhu, Y. Yuan, C. Rorres, and M. Kam, Distributed M-ary hypothesis testing with binary local decisions, Information Fusion, vol.5, issue.3, pp.157-167, 2004.
DOI : 10.1016/j.inffus.2003.10.004

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.84.2395

G. Vazquez-vilar, A. T. Campo, A. G. , and A. Martinez, Bayesian <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math> </inline-formula>-Ary Hypothesis Testing: The Meta-Converse and Verd??-Han Bounds Are Tight, IEEE Transactions on Information Theory, vol.62, issue.5, pp.2324-2333, 2016.
DOI : 10.1109/TIT.2016.2542080

P. Moulin, Asymptotically achievable error probabilities for multiple hypothesis testing, 2016 IEEE International Symposium on Information Theory (ISIT), pp.1541-1545, 2016.
DOI : 10.1109/ISIT.2016.7541557

C. C. Leang and D. H. Johnson, On the asymptotics of M-hypothesis Bayesian detection, IEEE Transactions on Information Theory, vol.43, issue.1, pp.280-282, 1997.
DOI : 10.1109/18.567705

M. Naghshvar and T. Javidi, Active sequential hypothesis testing, The Annals of Statistics, vol.41, issue.6, pp.2703-2738, 2013.
DOI : 10.1214/13-AOS1144SUPP

URL : http://arxiv.org/abs/1203.4626

M. Nussbaum and A. Szko-la, The Chernoff lower bound for symmetric quantum hypothesis testing, The Annals of Statistics, vol.37, issue.2, pp.1040-1057, 2009.
DOI : 10.1214/08-AOS593

K. Audenaert, M. Nussbaum, A. Szko, and F. Verstraete, Asymptotic Error Rates in Quantum Hypothesis Testing, Communications in Mathematical Physics, vol.9, issue.1, pp.251-283, 2008.
DOI : 10.1007/s00220-008-0417-5

T. Ogawa and H. Nagaoka, Strong Converse and Stein's Lemma in Quantum Hypothesis Testing, IEEE Transactions on Information Theory, vol.46, issue.7, pp.2428-2433, 2000.
DOI : 10.1142/9789812563071_0003

URL : http://arxiv.org/abs/quant-ph/9906090

S. Zhu and B. Chen, Distributed detection over connected networks via one-bit quantizer, 2016 IEEE International Symposium on Information Theory (ISIT), pp.1526-1530, 2016.
DOI : 10.1109/ISIT.2016.7541554

N. Tishbi, F. Pereira, and W. Bialek, the information bottleneck method, Proc. of the 37-th Annual Allerton Conference on Coomunication, Control and Computing, pp.368-377, 1999.

C. R. Shalizi and J. P. Crutchfield, INFORMATION BOTTLENECKS, CAUSAL STATES, AND STATISTICAL RELEVANCE BASES: HOW TO REPRESENT RELEVANT INFORMATION IN MEMORYLESS TRANSDUCTION, Advances in Complex Systems, pp.91-95, 2002.
DOI : 10.1142/S0219525902000481

S. Gordon, H. Greenspan, and J. Goldberger, Applying the information bottleneck principle to unsupervised clustering of discrete and continuous image representations, Proceedings Ninth IEEE International Conference on Computer Vision, pp.370-377, 2003.
DOI : 10.1109/ICCV.2003.1238368

J. Goldberger, H. Greenspan, and S. Gordon, Unsupervised Image Clustering Using the Information Bottleneck Method, Joint Pattern Recognition Symposium, pp.158-165, 2002.
DOI : 10.1007/3-540-45783-6_20

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.3503

A. Bardera, J. Rigau, I. Boada, M. Feixas, and M. Sbert, Image Segmentation Using Information Bottleneck Method, IEEE Transactions on Image Processing, vol.18, issue.7, pp.1601-1612, 2009.
DOI : 10.1109/TIP.2009.2017823

URL : http://dugi-doc.udg.edu//bitstream/10256/3054/1/277.pdf

S. Chiappino, L. Marcenaro, and C. S. Regazzoni, Information Bottleneck-based relevant knowledge representation in large-scale video surveillance systems, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4364-4368, 2014.
DOI : 10.1109/ICASSP.2014.6854426

N. Slonim and N. Tishby, The power of word clusters for text classification, 23rd European Colloquium on Information Retrieval Research, p.200, 2001.

M. Wang, Y. He, and M. Jiang, Text categorization of Enron email corpus based on information bottleneck and maximal entropy, IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, pp.2472-2475, 2010.
DOI : 10.1109/ICOSP.2010.5656737

N. Tishby and N. Zaslavsky, Deep learning and the information bottleneck principle, 2015 IEEE Information Theory Workshop (ITW), pp.1-5, 2015.
DOI : 10.1109/ITW.2015.7133169

URL : http://arxiv.org/abs/1503.02406

K. Rose, Deterministic annealing for clustering, compression, classification, regression, and related optimization problems, Proceedings of the IEEE, pp.2210-2239, 1998.
DOI : 10.1109/5.726788

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.3047

N. Slonim, N. Friedman, and N. Tishby, Unsupervised document classification using sequential information maximization, Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '02, pp.129-136, 2002.
DOI : 10.1145/564376.564401

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.5598

D. Vijayasenan, F. Valente, and H. Bourlard, Agglomerative information bottleneck for speaker diarization of meetings data, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU), pp.250-255, 2007.
DOI : 10.1109/ASRU.2007.4430119

R. Ahlswede, P. Gács, and J. Körner, Bounds on conditional probabilities with applications in multi-user communication, Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete, pp.157-177, 1976.
DOI : 10.1007/BF00535682

C. E. Shannon, A Mathematical Theory of Communication, Bell System Technical Journal, vol.27, issue.3, pp.379-423, 1948.
DOI : 10.1002/j.1538-7305.1948.tb01338.x

R. Fano, Class notes for transmission of information, course 6, Massachusetts Institute of Technology, Tech. Rep, vol.574

J. Wolfowitz, The coding of messages subject to chance errors, Illinois Journal of Mathematics, vol.1, issue.4, pp.591-606, 1957.

I. Csiszar and J. Körner, Information theory: coding theorems for discrete memoryless systems, 2011.
DOI : 10.1017/CBO9780511921889

J. C. Kie?er, Strong converses in source coding relative to a fidelity criterion, IEEE Transactions on Information Theory, vol.37, issue.2, pp.257-262, 1991.

G. Dueck, The strong converse to the coding theorem for the multiple?access channel, J. Comb. Inform. Syst. Sci, vol.6, issue.3, pp.187-196, 1981.

B. Kelly and A. Wagner, Reliability in source coding with side information Information Theory, IEEE Transactions on, vol.58, issue.8, pp.5086-5111, 2012.
DOI : 10.1109/tit.2012.2201346

URL : http://arxiv.org/abs/1109.0923

G. Katz, P. Piantanida, and M. Debbah, Distributed Binary Detection with Lossy Data Compression ArXiv e-prints, IEEE Trans. on, 2016.
DOI : 10.1109/tit.2017.2688348

URL : http://arxiv.org/abs/1601.01152

G. Katz, P. Piantanida, R. Couillet, and M. Debbah, Joint estimation and detection against independence, 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton)
DOI : 10.1109/ALLERTON.2014.7028594

URL : https://hal.archives-ouvertes.fr/hal-01098853

G. Katz, P. Piantanida, and M. Debbah, Collaborative distributed hypothesis testing with general hypotheses, 2016 IEEE International Symposium on Information Theory (ISIT), 2016.
DOI : 10.1109/ISIT.2016.7541590

URL : https://hal.archives-ouvertes.fr/hal-01436846

P. Piantanida, L. R. Vega, and A. Hero, A proof of the Generalized Markov Lemma with countable infinite sources, 2014 IEEE International Symposium on Information Theory, 2014.
DOI : 10.1109/ISIT.2014.6874901

URL : https://hal.archives-ouvertes.fr/hal-01093440

R. Ahlswede and J. Korner, Source coding with side information and a converse for degraded broadcast channels, IEEE Transactions on Information Theory, vol.21, issue.6, pp.629-637, 1975.
DOI : 10.1109/TIT.1975.1055469

S. Ho and S. Verdu, On the interplay between conditional entropy and error probability Information Theory, IEEE Transactions on, vol.56, issue.12, pp.5930-5942, 2010.

L. R. Vega, P. Piantanida, and A. O. Hero, The three-terminal interactive lossy source coding problem, Information Theory IEEE Trans. on, p.2015
URL : https://hal.archives-ouvertes.fr/hal-01093470

T. Linder, G. Lugosi, and K. Zeger, Fixed-rate universal lossy source coding and rates of convergence for memoryless sources Information Theory, IEEE Trans. on, vol.41, issue.3, pp.665-676, 1995.

G. V. Moustakides and V. V. Veeravalli, Sequentially detecting transitory changes, 2016 IEEE International Symposium on Information Theory (ISIT), pp.26-30, 2016.
DOI : 10.1109/ISIT.2016.7541254

B. K. Guépié, L. Fillatre, and I. Nikiforov, Sequential Detection of Transient Changes, Sequential Analysis, vol.24, issue.4, pp.528-547, 2012.
DOI : 10.1109/TSP.2005.857060

E. Ebrahimzadeh and A. Tchamkerten, Sequential detection of transient changes in stochastic systems under a sampling constraint, 2015 IEEE International Symposium on Information Theory (ISIT), pp.156-160, 2015.
DOI : 10.1109/ISIT.2015.7282436

P. O. Vontobel, A generalized Blahut-Arimoto algorithm, IEEE International Symposium on Information Theory, 2003. Proceedings., p.53, 2003.
DOI : 10.1109/ISIT.2003.1228067

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.2567

H. H. Permuter and I. Naiss, Extension of the Blahut-Arimoto algorithm for maximizing directed information, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp.1442-1449, 2010.
DOI : 10.1109/ALLERTON.2010.5707083

I. Sanov, On the probability of large deviations of random variables, United States Air Force Office of Scientific Research, 1958.

J. Villard and P. Piantanida, Secure multiterminal source coding with side information at the eavesdropper Information Theory, IEEE Transactions on, vol.59, issue.6, pp.3668-3692, 2013.

A. Gamal and Y. Kim, Network information theory, 2011.
DOI : 10.1017/CBO9781139030687

A. Schrijver, Theory of linear and integer programming, 1998.

G. A. Margulis, Probabilistic characteristics of graphs with large connectivity, Problemy Pereda?i Informacii, vol.10, issue.2, pp.101-108, 1974.