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Thermal Estimation for 3D-ICs through Generative Networks. 2023 IEEE INTERNATIONAL 3D SYSTEMS INTEGRATION CONFERENCE, 3DIC. https://doi.org/10.1109/3DIC57175.2023.10154977 Abdelkhalek, M., Baron, D., & Wong, C.-W. (2022). Mismatched Estimation in the Distance Geometry Problem. 2022 56TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, pp. 1031–1035. https://doi.org/10.1109/IEEECONF56349.2022.10051876 Kashyap, P., Choi, Y., Dey, S., Baron, D., Wong, C.-W., Wu, T., … Franzon, P. D. (2022). Modeling of Adaptive Receiver Performance Using Generative Adversarial Networks. IEEE 72ND ELECTRONIC COMPONENTS AND TECHNOLOGY CONFERENCE (ECTC 2022), pp. 1958–1963. https://doi.org/10.1109/ECTC51906.2022.00307 Kashyap, P., Gajjar, A., Choi, Y., Wong, C.-W., Baron, D., Wu, T., … Franzon, P. (2022). RxGAN: Modeling High-Speed Receiver through Generative Adversarial Networks. MLCAD '22: PROCEEDINGS OF THE 2022 ACM/IEEE 4TH WORKSHOP ON MACHINE LEARNING FOR CAD (MLCAD), pp. 167–172. https://doi.org/10.1145/3551901.3556480 Goenka, R., Cao, S.-J., Wong, C.-W., Rajwade, A., & Baron, D. (2021). CONTACT TRACING ENHANCES THE EFFICIENCY OF COVID-19 GROUP TESTING. 2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), pp. 8168–8172. https://doi.org/10.1109/ICASSP39728.2021.9414034 Kashyap, P., Pitts, W. S., Baron, D., Wong, C.-W., Wu, T., & Franzon, P. D. (2021). High Speed Receiver Modeling Using Generative Adversarial Networks. IEEE 30TH CONFERENCE ON ELECTRICAL PERFORMANCE OF ELECTRONIC PACKAGING AND SYSTEMS (EPEPS 2021). https://doi.org/10.1109/EPEPS51341.2021.9609124 Ma, Y., Kang, M., Silversteint, J. W., & Baron, D. (2021). Local Convergence of an AMP Variant to the LASSO Solution in Finite Dimensions. 2021 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), pp. 2256–2261. https://doi.org/10.1109/ISIT45174.2021.9518079 Ma, A., Zhou, Y., Rush, C., Baron, D., & Needell, D. (2019). An Approximate Message Passing Framework for Side Information. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 67(7), 1875–1888. https://doi.org/10.1109/TSP.2019.2899286 Ma, Y., Rush, C., & Baron, D. (2019, November). Analysis of Approximate Message Passing With Non-Separable Denoisers and Markov Random Field Priors. IEEE TRANSACTIONS ON INFORMATION THEORY, Vol. 65, pp. 7367–7389. https://doi.org/10.1109/TIT.2019.2934152 Zhu, J., & Baron, D. (2018). Performance Limits With Additive Error Metrics in Noisy Multimeasurement Vector Problems. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 66(20), 5338–5348. https://doi.org/10.1109/TSP.2018.2866844 Zhu, J., Pilgrim, R., & Baron, D. (2017). An overview of multi-processor approximate message passing. 2017 51st Annual Conference on Information Sciences and Systems (CISS). Presented at the 2017 51st Annual Conference on Information Sciences and Systems (CISS). https://doi.org/10.1109/ciss.2017.7926166 Ma, Y. T., Rush, C., & Baron, D. (2017). Analysis of approximate message passing with a class of non-separable denoisers. 2017 ieee international symposium on information theory (isit), 231–235. https://doi.org/10.1109/isit.2017.8006524 Baron, D., Ma, A., Needell, D., Rush, C., & Woolf, T. (2017). Conditional approximate message passing with side information. 2017 51st Asilomar Conference on Signals, Systems, and Computers. Presented at the 2017 51st Asilomar Conference on Signals, Systems, and Computers. https://doi.org/10.1109/acssc.2017.8335374 Pilgrim, R., Zhu, J., Baron, D., & Bajwa, W. U. (2017). Generalized geometric programming for rate allocation in consensus. 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton). Presented at the 2017 55th Annual Allerton Conference on Communication, Control, and Computing (Allerton). https://doi.org/10.1109/allerton.2017.8262762 Ma, Y., Lu, Y. M., & Baron, D. (2017). Multiprocessor approximate message passing with column-wise partitioning. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Presented at the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). https://doi.org/10.1109/icassp.2017.7953061 Ma, Y., Zhu, J., & Baron, D. (2016). Approximate Message Passing Algorithm With Universal Denoising and Gaussian Mixture Learning. IEEE Transactions on Signal Processing, 64(21), 5611–5622. https://doi.org/10.1109/tsp.2016.2599484 Han, P. X., Zhu, J. N., Niu, R. X., & Baron, D. (2016). Multi-processor approximate message passing using lossy compression. International conference on acoustics speech and signal processing, 6240–6244. https://doi.org/10.1109/icassp.2016.7472877 Zhu, J., Baron, D., & Krzakala, F. (2017). Performance Limits for Noisy Multimeasurement Vector Problems. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 65(9), 2444–2454. https://doi.org/10.1109/tsp.2016.2646663 Zhu, J., Beirami, A., & Baron, D. (2016). Performance trade-offs in multi-processor approximate message passing. 2016 ieee international symposium on information theory, 680–684. https://doi.org/10.1109/isit.2016.7541385 Krishnan, N., & Baron, D. (2015). A Universal Parallel Two-Pass MDL Context Tree Compression Algorithm. IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 9(4), 741–748. https://doi.org/10.1109/jstsp.2015.2403800 Tan, J., Ma, Y., Rueda, H., Baron, D., & Arce, G. R. (2015). Approximate message passing in coded aperture snapshot spectral imaging. 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). Presented at the 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). https://doi.org/10.1109/globalsip.2015.7418268 Tan, J., Ma, Y., Rueda, H., Baron, D., & Arce, G. R. (2016). Compressive Hyperspectral Imaging via Approximate Message Passing. IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 10(2), 389–401. https://doi.org/10.1109/jstsp.2015.2500190 Tan, J., Ma, Y., & Baron, D. (2015). Compressive Imaging via Approximate Message Passing With Image Denoising. IEEE Transactions on Signal Processing, 63(8), 2085–2092. https://doi.org/10.1109/tsp.2015.2408558 Trussell, H. J., & Baron, D. (2015). Creating Analytic Online Homework for Digital Signal Processing [sp Education]. IEEE Signal Processing Magazine, 32(5), 112–118. https://doi.org/10.1109/msp.2015.2438992 Ma, Y. T., Baron, D., & Beirami, A. (2015). Mismatched estimation in large linear systems. 2015 ieee international symposium on information theory (isit), 760–764. https://doi.org/10.1109/isit.2015.7282557 Zhu, J., Baron, D., & Duarte, M. F. (2015). Recovery From Linear Measurements With Complexity-Matching Universal Signal Estimation. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 63(6), 1512–1527. https://doi.org/10.1109/tsp.2015.2393845 Krishnan, N., Baron, D., & Mihcak, M. K. (2014). A Parallel two-pass MDL context tree algorithm for universal source coding. 2014 ieee international symposium on information theory (isit), 1862–1865. https://doi.org/10.1109/isit.2014.6875156 Zhu, J. N., Baron, D., & Duarte, M. F. (2014). Complexity-adaptive universal signal estimation for compressed sensing. 2014 IEEE Workshop on Statistical Signal Processing (SSP), 388–391. https://doi.org/10.1109/ssp.2014.6884657 Ma, Y., Zhu, J., & Baron, D. (2014). Compressed Sensing via Universal Denoising and Approximate Message Passing. Proc. 52d Allerton Conference on Communication, Control, and Computing. Monticello, IL. Tan, J., Ma, Y., & Baron, D. (2014). Compressive imaging via approximate message passing with wavelet-based image denoising. 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP). Presented at the 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP). https://doi.org/10.1109/globalsip.2014.7032152 Ma, Y., Tan, J., Krishnan, N., & Baron, D. (2014). Empirical Bayes and Full Bayes for Signal Estimation. ArXiv:1405.2113 [Cs, Math]. Retrieved from http://arxiv.org/abs/1405.2113 Krishnan, N., & Baron, D. (2014). Performance of parallel two-pass MDL context tree algorithm. 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP). Presented at the 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP). https://doi.org/10.1109/globalsip.2014.7032133 Tan, J., Carmon, D., & Baron, D. (2014). Signal Estimation With Additive Error Metrics in Compressed Sensing. IEEE TRANSACTIONS ON INFORMATION THEORY, 60(1), 150–158. https://doi.org/10.1109/tit.2013.2285214 Tan, J., Baron, D., & Dai, L. Y. (2014). Signal estimation with low infinity-norm error by minimizing the mean p-norm error. 2014 48th Annual Conference on Information Sciences and Systems (CISS). https://doi.org/10.1109/ciss.2014.6814074 Ma, Y., Baron, D., & Needell, D. (2014). Two-Part Reconstruction With Noisy-Sudocodes. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 62(23), 6323–6334. https://doi.org/10.1109/tsp.2014.2362892 Tan, J., Baron, D., & Dai, L. (2014). Wiener Filters in Gaussian Mixture Signal Estimation With l(infinity)-Norm Error. IEEE TRANSACTIONS ON INFORMATION THEORY, 60(10), 6626–6635. https://doi.org/10.1109/tit.2014.2345260 Duarte, M. F., Wakin, M. B., Baron, D., Sarvotham, S., & Baraniuk, R. G. (2013). Measurement Bounds for Sparse Signal Ensembles via Graphical Models. IEEE Transactions on Information Theory, 59(7), 4280–4289. https://doi.org/10.1109/tit.2013.2252051 Zhu, J. A., & Baron, D. (2013). Performance regions in compressed sensing from noisy measurements. 2013 47th Annual Conference on Information Sciences and Systems (CISS). https://doi.org/10.1109/ciss.2013.6552256 Tan, J., & Baron, D. (2013). Signal reconstruction in linear mixing systems with different error metrics. 2013 Information Theory and Applications Workshop (ITA). https://doi.org/10.1109/ita.2013.6502925 Baron, D., & Weissman, T. (2012). An MCMC Approach to Universal Lossy Compression of Analog Sources. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 60(10), 5230–5240. https://doi.org/10.1109/tsp.2012.2206585 Tan, J., Carmon, D., & Baron, D. (2012). Optimal estimation with arbitrary error metrics in compressed sensing. 2012 IEEE Statistical Signal Processing Workshop (ssp), 588–591. https://doi.org/10.1109/ssp.2012.6319767 Baron, D., & Jacob, T. (2012). Variable Length Compression of Codeword Indices for Lossy Compression. IEEE SIGNAL PROCESSING LETTERS, 19(12), 849–852. https://doi.org/10.1109/lsp.2012.2223462 Bickson, D., Baron, D., Ihler, A., Avissar, H., & Dolev, D. (2011). Fault Identification Via Nonparametric Belief Propagation. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 59(6), 2602–2613. https://doi.org/10.1109/tsp.2011.2116014 Baron, D. (2011). Information complexity and estimation. Fourth Workshop Inf. Theoretic Methods Science Eng. Presented at the WITMSE 2011. Baron, D., & Duarte, M. F. (2011). Universal MAP estimation in compressed sensing. 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton). Presented at the 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton). https://doi.org/10.1109/allerton.2011.6120245 Baron, D., & Weissman, T. (2010). An MCMC Approach to Lossy Compression of Continuous Sources. 2010 Data Compression Conference. Presented at the 2010 Data Compression Conference. https://doi.org/10.1109/dcc.2010.11 Baron, D., Sarvotham, S., & Baraniuk, R. G. (2010). Bayesian Compressive Sensing Via Belief Propagation. IEEE Transactions on Signal Processing, 58(1), 269–280. https://doi.org/10.1109/tsp.2009.2027773 Guo, D., Baron, D., & Shamai, S. (2009). A single-letter characterization of optimal noisy compressed sensing. 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton). Presented at the 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton 2009). https://doi.org/10.1109/allerton.2009.5394838 Baron, D., Duarte, M. F., Wakin, M. B., Sarvotham, S., & Baraniuk, R. G. (2009). Distributed Compressive Sensing. https://doi.org/10.21236/ada521228 Chandrasekaran, V., Wakin, M. B., Baron, D., & Baraniuk, R. G. (2009). Representation and Compression of Multidimensional Piecewise Functions Using Surflets. IEEE Transactions on Information Theory, 55(1), 374–400. https://doi.org/10.1109/tit.2008.2008153 Duarte, M. F., Sarvotham, S., Baron, D., Wakin, M. B., & Baraniuk, R. G. (2008). Performance Limits for Jointly Sparse Signals via Graphical Models. Proceedings of Sensor, Signal, and Information Processing Workshop. Presented at the SenSIP. Rachlin, Y., & Baron, D. (2008). The secrecy of compressed sensing measurements. 2008 46th Annual Allerton Conference on Communication, Control, and Computing. Presented at the 2008 46th Annual Allerton Conference on Communication, Control, and Computing. https://doi.org/10.1109/allerton.2008.4797641 Duarte, M. F., Sarvotham, S., Wakin, M. B., Baron, D., & Baraniuk, R. G. (2008). Theoretical Performace Limits for Jointly Sparse Signals via Graphical Models (Technical Report No. ECE-0802). Electrical and Computer Engineering Department, Rice University. Takhar, D., Laska, J. N., Wakin, M. B., Duarte, M. F., Baron, D., Sarvotham, S., … Baraniuk, R. G. (2006). A new compressive imaging camera architecture using optical-domain compression. In C. A. Bouman, E. L. Miller, & I. Pollak (Eds.), Computational Imaging IV. https://doi.org/10.1117/12.659602 Wakin, M. B., Laska, J. N., Duarte, M. F., Baron, D., Sarvotham, S., Takhar, D., … Baraniuk, R. G. (2006). An Architecture for Compressive Imaging. 2006 International Conference on Image Processing. Presented at the 2006 International Conference on Image Processing. https://doi.org/10.1109/icip.2006.312577 Kirolos, S., Laska, J., Wakin, M., Duarte, M., Baron, D., Ragheb, T., … Baraniuk, R. (2006). Analog-to-Information Conversion via Random Demodulation. 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software. Presented at the 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software. https://doi.org/10.1109/dcas.2006.321036 Baron, D., Sarvotham, S., & Baraniuk, R. G. (2006). Coding vs. Packet Retransmission over Noisy Channels. 2006 40th Annual Conference on Information Sciences and Systems. Presented at the 2006 40th Annual Conference on Information Sciences and Systems. https://doi.org/10.1109/ciss.2006.286528 Sarvotham, S., Baron, D., & Baraniuk, R. G. (2006). Compressed Sensing Reconstruction via Belief Propagation (Technical Report No. ECE-0601). Electrical and Computer Engineering Department, Rice University. Wakin, M. B., Laska, J. N., Duarte, M. F., Baron, D., Sarvotham, S., Takhar, D., … Baraniuk, R. G. (2006). Compressive Imaging for Video Representation and Coding. Proceedings of Picture Coding Symposium. Presented at the PCS. Duarte, M. F., Sarvotham, S., Baron, D., Wakin, M. B., & Baraniuk, R. G. (2006). Distributed Compressed Sensing of Jointly Sparse Signals. Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005. Presented at the Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005. https://doi.org/10.1109/acssc.2005.1600024 Baron, D., & Baraniuk, R. G. (2006). Faster sequential universal coding via block partitioning. IEEE Transactions on Information Theory, 52(4), 1708–1710. https://doi.org/10.1109/tit.2006.871041 Sarvotham, S., Baron, D., & Baraniuk, R. G. (2006). Measurements vs. Bits: Compressed Sensing meets Information Theory. Proceedings of 44th Allerton Conference on Communication, Control, and Computing. Monticello, IL. Tropp, J. A., Wakin, M. B., Duarte, M. F., Baron, D., & Baraniuk, R. G. (2006). Random Filters for Compressive Sampling and Reconstruction. 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings. Presented at the 2006 IEEE International Conference on Acoustics Speed and Signal Processing. https://doi.org/10.1109/icassp.2006.1660793 Sarvotham, S., Baron, D., & Baraniuk, R. G. (2006). Sudocodes – Fast Measurement and Reconstruction of Sparse Signals. 2006 IEEE International Symposium on Information Theory. Presented at the 2006 IEEE International Symposium on Information Theory. https://doi.org/10.1109/isit.2006.261573 Duarte, M. R., Wakin, M. B., Baron, D., & Baraniuk, R. G. (2006). Universal distributed sensing via random projections. 2006 5th International Conference on Information Processing in Sensor Networks. Presented at the The Fifth International Conference on Information Processing in Sensor Networks. https://doi.org/10.1109/ipsn.2006.244161 Sarvotham, S., Baron, D., & Baraniuk, R. G. (2006). Variable-Rate Universal Slepian-Wolf Coding with Feedback. Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005. Presented at the Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005. https://doi.org/10.1109/acssc.2005.1599690 Baron, D., Duarte, M. F., Sarvotham, S., Wakin, M. B., & Baraniuk, R. G. (2005). An Information-Theoretic Approach to Distributed Compressed Sensing. Proceedings of 43d Allerton Conference on Communication, Control, and Computing. Monticello, IL. Sarvotham, S., Wakin, M. B., Baron, D., Duarte, M. F., & Baraniuk, R. G. (2005). Analysis of the DCS One-Stage Greedy Algorithm for Common Sparse Supports (Technical Report No. ECE-05-03). Electrical and Computer Engineering Department, Rice University. Baron, D., & Bresler, Y. (2005). Antisequential Suffix Sorting for BWT-Based Data Compression. IEEE Transactions on Computers, 54(4), 385–397. https://doi.org/10.1109/tc.2005.56 Baron, D., Khojastepour, M. A., & Baraniuk, R. G. (2005). How quickly can we approach channel capacity? Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. Presented at the Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004. https://doi.org/10.1109/acssc.2004.1399310 Duarte, M. F., Sarvotham, S., Wakin, M. B., Baron, D., & Baraniuk, R. G. (2005). Joint Sparsity Models for Distributed Compressed Sensing. Online Proceedings of the Workshop on Signal Processing with Adaptive Sparse Structured Representations. Presented at the SPARS. Sarvotham, S., Baron, D., & Baraniuk, R. G. (2005). Non-Asymptotic Performance of Symmetric Slepian-Wolf Coding. Proceedings of 39th Annual Conference on Information Sciences and Systems. Presented at the CISS 2005. Wakin, M. B., Sarvotham, S., Duarte, M. F., Baron, D., & Baraniuk, R. G. (2005). Recovery of Jointly Sparse Signals from Few Random Projections. Proceedings of Workshop on Neural Information Processing Systems. Vancouver, Canada. Sarvotham, S., Baron, D., & Baraniuk, R. G. (2005). Variable-Rate Coding with Feedback for Universal Communication Systems. Proceedings of 43d Allerton Conference on Communication, Control, and Computing. Monticello, IL. Baron, D., & Bresler, Y. (2004). An O(N) Semipredictive Universal Encoder via the BWT. IEEE Transactions on Information Theory, 50(5), 928–937. https://doi.org/10.1109/tit.2004.826664 Chandrasekaran, V., Wakin, M., Baron, D., & Baraniuk, R. G. (2004). Compressing Piecewise Smooth Multidimensional Functions Using Surflets: Rate-Distortion Analysis [Technical Report]. Electrical and Computer Engineering Department, Rice University. Chandrasekaran, V., Wakin, M., Baron, D., & Baraniuk, R. G. (2004). Compression of Higher Dimensional Functions Containing Smooth Discontinuities. Proceedings of 38th Annual Conference on Information Sciences and Systems. Presented at the CISS 2004. Baron, D., Singer, A., & Baraniuk, R. G. (2004). Probability Assignments with Worst-Case Coding Length Constraints. Proceedings of 38th Annual Conference on Information Sciences and Systems. Presented at the CISS 2004. Baron, D., Khojastepour, M. A., & Baraniuk, R. G. (2004). Redundancy Rates of Slepian-Wolf Coding. Proceedings of 42d Allerton Conference on Communication, Control, and Computing. Monticello, IL. Chandrasekaran, V., Wakin, M. B., Baron, D., & Baraniuk, R. G. (2004). Surflets: a sparse representation for multidimensional functions containing smooth discontinuities. International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings. Presented at the International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings. https://doi.org/10.1109/isit.2004.1365602 Baron, D., Bresler, Y., & Mihcak, M. K. (2003). Two-Part Codes with Low Worst-Case Redundancies for Distributed Compression of Bernoulli Sequences. Proceedings of 37th Annual Conference on Information Sciences and Systems. Presented at the CISS 2003. Baron, D., & Birk, Y. (2002). Coding schemes for multislot messages in multichannel ALOHA with deadlines. IEEE Transactions on Wireless Communications, 1(2), 292–301. https://doi.org/10.1109/7693.994823 Baron, D., & Birk, Y. (2002). Multiple Working Points in Multichannel ALOHA with Deadlines. Wireless Networks, 8(1), 5–11. Baron, D., & Bresler, Y. (2001). Linear Complexity MDL Universal Coding with the BWT (Technical Report No. UILU-ENG-01-2213). Coordinated Science Laboratory, University of Illinois. Baron, D., & Bresler, Y. (2001, June). Linear Complexity MDL Universal Coding with the BWT. Presented at the Recent Results Session, IEEE International Symposium on Information Theory (ISIT2001). Baron, D., & Birk, Y. (2001). Multiround Coding and Coding-Reservation for Multislot Messages in Multichannel ALOHA with Deadlines (Technical Report No. EE Pub 1293). Electrical Engineering Department, Technion. Baron, D., & Singer, A. C. (2001). On the cost of worst case coding length constraints. IEEE Transactions on Information Theory, 47(7), 3088–3090. https://doi.org/10.1109/18.959291 Birk, Y., & Baron, D. (2000). Capacity Maximization in Multichannel Slotted ALOHA with Deadlines - an Overview (Technical Report No. EE Pub 1248, CCIT Report 314). Electrical Engineering Department, Technion. Baron, D., & Birk, Y. (2000). Coding Schemes for Multislot Messages in Multichannel ALOHA with Deadlines (Technical Report No. EE Pub 1241, CIT Report 307). Electrical Engineering Department, Technion. Baron, D., & Birk, Y. (2000). Multiple Working Points in Multichannel ALOHA with Deadlines (Technical Report No. EE Pub 1240, CCIT Report 306). Electrical Engineering Department, Technion. Baron, D., & Birk, Y. (2000). On the Merits of Impure Multi-Copy Schemes for MultiChannel Slotted ALOHA with Deadlines (Technical Report No. EE Pub 1249, CCIT Report 315). Electrical Engineering Department, Technion. Baron, D., & Bresler, Y. (2000). Tree Source Identification with the Burrows Wheeler Transform. Proceedings of 34th Annual Conference on Information Sciences and Systems, 2, FA1–10 - FS1–15. Princeton, NJ. Baron, D., & Birk, Y. (1999). On the use of Multiple Working Points in Multichannel ALOHA with Deadlines. Proceedings of 37th Allerton Conference on Communication, Control, and Computing, 728–737. Monticello, IL.