By Topic

Terahertz

  1. Graph Neural Network Based Hybrid Beamforming Design in Wideband Terahertz MIMO-OFDM Systems,“
    B. Li and M. Vu, IEEE International Symposium on Phased Array Systems and Technology, to appear, 2024.

Satellite Communications

  1. Interference Analysis for Coexistence of Terrestrial Networks with Satellite Services,“
    B. Lim and M.Vu, IEEE Transactions on Wireless Communications, April 2024.

Reconfigurable Intelligent Surface-Assisted Communications

  1. Joint User Selection and Beamforming Design for Multi-IRS aided Internet-of-Things Networks,“
    S. Yoon, B. Lim, M. Vu, and Y. Ko, IEEE Transactions on Vehicular Technology, February 2024.
  2. Joint Active-Passive Beamforming and User Association in IRS-Assisted mmWave Cellular Networks,”
    E. M. Taghavi, R. H., A. Alizadeh, N. Rajatheva, M. Vu, and M. Latva-aho, IEEE Transactions on Vehicular Technology, Aug. 2023.
  3. Graph Neural Network Based Beamforming and RIS Reflection Design in A Multi-RIS Assisted Wireless Network,”
    B. Lim and M. Vu, 23rd IEEE Statistical Signal Processing (SSP) workshop, July 2023.
  4. Low Complexity Joint User Association, Beamforming and RIS Reflection Optimization for Load Balancing in a Multi-RIS Assisted Network,”
    B. Lim, A. Alizadeh, and M. Vu, IEEE Wireless Communications and Networking Conf. (WCNC), Mar. 2023.
  5. Joint Multi-User Channel Estimation for Hybrid Reconfigurable Intelligent Surfaces,”
    B. Boiadjieva and M. Vu, IEEE Int’l Conf. on Communications (ICC), May 2023.

User Associations for 5G mmWave networks

  1. Multi-Agent Q-Learning for Real-Time Load Balancing User Association and Handover in Mobile Networks,” 
    A. Alizadeh, B. Lim and M.Vu, IEEE Transactions on Wireless Communications, Aug. 2024.
  2. Joint Active-Passive Beamforming and User Association in IRS-Assisted mmWave Cellular Networks,”
    E. M. Taghavi, R. H., A. Alizadeh, N. Rajatheva, M. Vu, and M. Latva-aho, IEEE Transactions on Vehicular Technology, Aug. 2023.
  3. Distributed Multi-Agent Deep Q-Learning for Load Balancing User Association in Dense Networks,”
    B. Lim and M. Vu, IEEE Wireless Communications Letters, July 2023.
  4. Low Complexity Joint User Association, Beamforming and RIS Reflection Optimization for Load Balancing in a Multi-RIS Assisted Network,”
    B. Lim, A. Alizadeh, and M. Vu, IEEE Wireless Communications and Networking Conf. (WCNC), Mar. 2023.
  5. Reinforcement Learning for User Association and Handover in mmWave-enabled Networks,”
    A. Alizadeh and M. Vu, IEEE Transactions on Wireless Communications, vol. 21, no. 11, pp. 9712 – 9728, Nov. 2022.
  6. Joint User Association and Caching in Wireless Heterogeneous Networks with Backhaul,”
    Y. Liu, A. Alizadeh, M. Vu, and E. Yeh, IEEE Int’l Conf. on Communications (ICC), Montreal, June 2021.
  7. Distributed User Association in 5G Networks Using Early Acceptance Matching Games,”
    A. Alizadeh and M. Vu, IEEE Transactions for Wireless Communications, Vol. 20, No. 4, pp. 2428 – 2441, April 2021.
  8. “Multi-Armed Bandit Load Balancing User Association in 5G Cellular HetNets,”
    A. Alizadeh and M. Vu, IEEE Global Communications Conf. (GLOBECOM), Taiwan, Dec. 2020.
  9. “Early Acceptance Matching Game for User Association in 5G Cellular HetNets,”
    A. Alizadeh and M. Vu, IEEE Global Communications Conf. (GLOBECOM), Hawaii, Dec. 2019.
  10. “A Study of Interference Distributions in Millimeter Wave Cellular Networks,”
    A. Alizadeh, M. Vu, and T. S. Rappaport,  biennial IEEE Conf. on Microwaves, Communications, Antennas & Electronic Systems (IEEE COMCAS), Nov. 2019.
  11. “Load Balancing User Association in Millimeter Wave MIMO Networks,”
    A. Alizadeh and Mai Vu, IEEE Transactions on Wireless Communications, vol. 18, no. 6, pp. 2932-2945, Jun. 2019.
  12. “Time-Fractional User Association in Millimeter Wave MIMO Networks,”
    A. Alizadeh and Mai Vu, IEEE International Conference on Communications (IEEE ICC 2018), May 2018

Wireless Power Transfer and Mobile Edge Computing

  1. Energy-efficient Joint Wireless Charging and Computation Offloading In MEC Systems,”
    R. Malik and M. Vu, IEEE Journal of Selected Topics in Signal Processing, vol. 15, no. 5, pp. 1110-1126, Aug. 2021.
  2. On-Request Wireless Charging and Partial Computation Offloading In Multi-Access Edge Computing Systems,”
    R. Malik and M. Vu, IEEE Transactions on Wireless Communications, vol. 20, no. 10, pp. 6665-6679, Oct. 2021.
  3. “Energy-Efficient Computation Offloading in Delay-Constrained Massive MIMO Enabled Edge Network Using Data Partitioning,”
    R. Malik and M. Vu, IEEE Transactions on Wireless Communications, Volume: 19, Issue: 10 , pp. 6977 – 6991, Oct. 2020.
  4. “Multi-Access Edge Computation Offloading Using Massive MIMO,” 
    R. Malik and M. Vu, IEEE Global Communications Conf. (GLOBECOM), Hawaii, Dec. 2019.
  5. “Optimal Transmission Using a Self-sustained Relay in a Full-Duplex MIMO System,”
    R. Malik and Mai Vu, IEEE Journal on Selected Areas in Communications, vol. 37, no. 2, pp. 374-390, Feb. 2019.
  6. “Optimizing Throughput in a MIMO System with a Self-sustained Relay and Non-uniform Power Splitting,”
    R. Malik and Mai Vu, IEEE Wireless Communications Letters, vol. 8, no. 1, pp. 205-208, Feb. 2019.

Unequal Error Protection in Short Block Length Codes

  1. Metrics and Algorithms for Designing Convolutional Codes with Unequal Error Protection,”
    M. Karimzadeh and M. Vu, IEEE Transactions on Vehicular Technology, accepted 2021, vol. 70, no. 11, pp. 11169-11183, Nov. 2021.
  2. SIVA: A Low Complexity and Optimum Decoding Algorithm for Tail-biting Codes,”
    M. Karimzadeh and M. Vu, IEEE Transactions for Wireless Communications, vol. 20, no. 9, pp. 5957-5968, Sept. 2021.
  3. “Optimal CRC Design and Serial List Viterbi Decoding for Multi-Input Convolutional Codes,”
    M. Karimzadeh and M. Vu, IEEE Global Communications Conf. (GLOBECOM), Taiwan, Dec. 2020.
  4. “Short Blocklength Priority-Based Coding for Unequal Error Protection in the AWGN Channel,”
    M. Karimzadeh and M. Vu, IEEE Global Communications Conf. (GLOBECOM), Hawaii, Dec. 2019.

Interference Modeling and Cooperation in Cellular Networks

  1. “MIMO Cellular Networks Performance Under User-Assisted Relaying,”
    H.E.Elkotby and Mai Vu, IEEE Transactions on Wireless Communications, vol. 17, no. 11, pp. 7144-7158, Nov. 2018.
  2. “Interference Modeling for Cellular Networks under Beamforming Transmission,”
    H. Elkotby and M. Vu, IEEE Transactions on Wireless Communications, vol. 16, no. 8, pp. 5201-5217, Aug. 2017.
  3. A Mixture Model for NLOS mmWave Interference Distribution,”
    H. E. Elkotby and M. Vu, accepted to Globecom, 2016.
  4. A probabilistic Interference Distribution Model Encompassing Cellular LOS and NLOS mmWave Propagation,”
    H. E. Elkotby and M. Vu, accepted to GlobalSIP, 2016.
  5. Uplink User-Assisted Relaying Deployment in Cellular Networks,”
    H. E. Elkotby and M. Vu, IEEE Trans. on Wireless Communications, vol. 14, no. 10, pp. 5468-5483, Oct. 2015.
  6. Outage Performance of Uplink User-Assisted Relaying in 5G Cellular Networks,”
    H. E. Elkotby and M. Vu, Globecom, 2015.
  7. Interference and Throughput Analysis of Uplink User-Assisted Relaying in Cellular Networks,”
    H. ElKotby and M. Vu, IEEE 25th Int’l Symp. on Personal, Indoor and Mobile Radio Commun. (PIMRC), Washington DC, Sept. 2014.

Big Data Analytics

  1. “Efficient Search for Multi-Scale Time Delay Correlations in Big Time Series Data,”
    H. Nguyen, T.B. Pedersen, V.L. Ho, M. Vu, 23rd International Conference on Extending Database Technology (EDBT), Denmark, Mar. 2020.
  2. “AMIC: An Adaptive Information Theoretic Method to Identify Multi-Scale Temporal Correlations in Big Time Series Data,”
    N. Ho, H. Vo, M. Vu, T. B. Pedersen, accepted to IEEE Transactions on Big Data, vol. 7, no. 1, pp. 128-146, 1 March 2021.
  3. “Efficient Bottom-Up Discovery of Multi-Scale Time Series Correlations Using Mutual Information,”
    N. Ho, T. B. Pedersen, M. Vu, V. L. Ho, and C. A.N. Biscioz, 35th IEEE International Conference on Data Engineering, Apr. 2019.
  4. “An Adaptive Information-Theoretic Approach for Identifying Temporal Correlations in Big Data Sets,”
    N. Ho, H. Vo, and Mai Vu, IEEE International Conference on Big Data (IEEE BigData 2016), Dec 2016.

Link-State based Optimization

  1. Link Regimes Analysis for Partial Decode-Forward Two-Way Relay Transmission,”
    A. Al Haija, P. Zhong and M. Vu, IEEE Transactions on Communications, vol. 65, no. 5, pp. 1925-1939, May 2017.
  2. “Message Priority in Two-Way Decode-Forward Relaying,”
    L. Pinals, A. A. Al Haija, and M. Vu, Globecom, 2016.
  3. “Link Regime and Power Savings of Decode-Forward Relaying in Fading Channels,”
    L. Pinals, A. A. Al Haija, and M. Vu, IEEE Trans. on Communications, vol. 64, no. 3, pp. 931-946, March 2016.
  4. Link-State Optimized Decode-Forward Transmission for Two-Way Relaying,”
    L. Pinals and M. Vu, IEEE Trans. on Communications, vol. 64, no. 5, pp. 1844-1860, May 2016.
  5. “Maximum Entropy Quantization for Link-State Adaptation in Two-Way Relaying,”
    L. Pinals and M. Vu, MILCOM, 2015.
  6. “Relay Power Savings Through Independent Coding,”
    L. Pinals and M. Vu, Globecom, 2015.
  7. Link State Based Decode-Forward Schemes for Two-way Relaying,”
    L. Pinals and M. Vu, International Workshop on Emerging Technologies for 5G Wireless Cellular Networks (Globecom), Dec 2014.
  8. “Adaptation of Decode-Forward Two-Way Relaying to Fading Links: a Rate and Power Analysis,”
    L. Pinals and M. Vu, International Conference on Communications (ICC), June 2015.
  9. Decode-Forward Transmission for the Two-Way Relay Channels,”
    A. Al Haija, P. Zhong and M. Vu, submitted for publication, April 2015.

Reliability of Cooperative Transmission

  1. “Poster: Reliability enhancement in V2V networks through vehicle-assisted relaying,”
    H. E. Elkotby and M. Vu, IEEE Vehicular Networking Conference (VNC), 2016.
  2. “Outage Analysis and Power Savings for Independent and Coherent Decode-Forward Relaying,”
    A. Abu Al Haija, L. Pinals, and M. Vu, Globecom, 2015.
  3. “Outage Analysis for Coherent Decode-Forward Relaying over Rayleigh Fading Channels,”
    A. Abu Al Haija and M. Vu, IEEE Trans. Commu., vol. 63, no. 4, pp. 1162–1177, Apr. 2015.
  4. “Spectral Efficiency and Outage Performance for Hybrid D2D-Infrastructure Uplink Cooperation,”
    A. Abu Al Haija and M. Vu, IEEE Trans. Wireless Commu., vol. 14, no. 3, pp. 1183–1198, Mar. 2015.
  5. Rate Maximization for Half-Duplex Multiple Access with Cooperating Transmitters,
    A. Abu Al Haija and Mai Vu, IEEE Trans. on Comm., vol. 61, no. 9, pp. 3620 – 3634, Sept. 2013.
  6. “Outage Analysis for Half-Duplex Partial Decode-Forward Relaying over Fading Channel,”
    A. Abu Al Haija and M. Vu, IEEE GLOBECOM, Dec. 2014.
  7. “Uplink Outage Analysis for Mobile-to-Mobile Cooperation,”
    A. Abu Al Haija and M. Vu, D2D workshop, IEEE GLOBECOM, Dec. 2013.
  8. “A Half-Duplex Cooperative Scheme with Partial Decode-Forward Relaying,”
    A. Abu Al Haija and M. Vu, IEEE ISIT, July 2011.
  9. Joint Typicality Analysis for Half-Duplex Cooperative Communication,”
    A. Abu Al Haija and M. Vu, The 12th Canadian Workshop on Information Theory (CWIT), May 2011.

Energy-Efficient Wireless Communications

  1. “Modeling and Analysis of Energy Efficiency and Interference for Cellular Relay Deployment,”
    F. Parzysz, M. Vu, and F. Gagnon, IEEE Transactions on Wireless Communications, vol. 16, no. 2, pp. 982-997, Feb. 2017.
  2. Trade-offs on Energy-Efficient Relay Deployment in Cellular Networks,
    F. Parzysz, M. Vu, and F. Gagnon, IEEE Vehicular Technology Conf. VTC2014-Fall, Vancouver, Sept. 2014. 
  3. Impact of Propagation Environment on Energy-Efficient Relay Placement: Model and Performance Analysis,
    F. Parzysz, M. Vu, and F. Gagnon, IEEE Trans. on Wireless Communications, vol. 13 , no. 4 pp. 2214 – 2228, Apr. 2014. 
  4. Energy Minimization for the Half-Duplex Relay Channel with Decode-Forward Relaying,”
    F. Parzysz, M. Vu, and F. Gagnon, IEEE Trans. on Comm., vol. 61, no. 6, pp. 2232 – 2247, Jun 2013.
  5. Optimal Distributed Coding Schemes for Energy Efficiency in the Fading Relay Channel,” 
    F. Parzysz, M.Vu, F. Gagnon, IEEE Int’l Conf. on Comm. (ICC), June 2012.
  6. A Half-Duplex Relay Coding Scheme Optimized for Energy Efficiency,
    F. Parzysz, M.Vu, F. Gagnon, IEEE Information Theory Workshop, Oct 2011.
  7. Energy-Efficient Schemes for On-Demand Relaying,
    F. Parzysz, M.Vu, F. Gagnon, The 34th IEEE Sarnoff Symposium, May 2011.

Relay Coding Design

  1. “Short Blocklength Priority-Based Coding for Unequal Error Protection in the AWGN Channel,”
    M. Karimzadeh and M. Vu, IEEE Global Communications Conference, Dec 2019.
  2. Combined Decode-Forward and Layered Noisy Network Coding Schemes for Relay Channels,”
    P. Zhong and M. Vu, IEEE Int’l Symposium on Info. Theory (ISIT), July 2012.
  3. Partial Decode-forward Coding Schemes for the Gaussian Two-Way Relay Channel,
    P. Zhong and M. Vu, IEEE Int’l Conf. on Comm. (ICC), June 2012.
  4. On Compress-Forward without Wyner-Ziv Binning for Relay Networks,
    P. Zhong, A. Abu Al Haija and M. Vu, submitted to IEEE Trans. on Information Theory, Nov. 2011.
  5. Compress-Forward without Wyner-Ziv Binning for the One-Way and Two-Way Relay Channels,
    P. Zhong and M. Vu, Forty-Ninth Annual Allerton Conference, Sept 2011.
  6. Decode-forward and Compute-forward Coding Schemes for the Two-Way Relay Channel,
    P. Zhong and M. Vu, IEEE Information Theory Workshop, Oct 2011.

Relay Communications

  1. “Exhaustive Message Splitting Scheme for Partial Decode-Forward in A Three-Relay Network,”
    Y. Tang, A. Abu Al Haija and M. Vu,  the 48th Annual Conf. on Information Sciences and Systems (CISS), Mar 2014.
  2. An Asymptotically Capacity-Achieving Scheme for the Gaussian Relay Channel with Relay-Destination Cooperation,
    A. Abu Al Haija and M. Vu, 47th Annual Conf. on Information Sciences and Systems (CISS), Mar 2013.
  3. A Partial Decode-Forward Scheme For A Network with N relays,”
    Y. Tang and M. Vu, 47th Annual Conf. on Information Sciences and Systems (CISS), Mar 2013.
  4. Efficient Use of Joint Source-Destination Cooperation in the Gaussian Multiple Access Channel,
    A.Abu Al Haija and M. Vu, IEEE International Conference on Communications (ICC), June 2013.
  5. Partial decode-forward for quantum relay channels,”
    I. Savov, M. Wilde and M. Vu, IEEE Int’l Symposium on Info. Theory (ISIT), July 2012.
  6. Throughput-Optimal Half-Duplex Cooperative Scheme with Partial Decode-Forward Relaying”,
    A. Abu Al Haija and M. Vu, IEEE Int’l Conf. on Communications (ICC), June 2011.

Cognitive Communications and Networks

  1. A Half-Duplex Transmission Scheme for the Gaussian Causal Cognitive Interference Channel,
    Z. Wu and M. Vu, IEEE International Conf. on Comm. (ICC), June 2013.
  2. Partial Decode-Forward Binning for Full-Duplex Causal Cognitive Interference Channels,
    Z. Wu and M. Vu, IEEE Int’l Symposium on Info. Theory (ISIT), July 2012.
  3. On the Capacity of the Cognitive Z-Interference Channel,”
    M. Vaezi and M. Vu, The 12th Canadian Workshop on Information Theory (CWIT), May 2011.
  4. Capacity- and Bayesian-Based Cognitive Sensing with Location Side Information”,
    P. Jia, M. Vu, T. Le-Ngoc, S-C. Hong, V. Tarokh, IEEE Trans. on Selected Areas in Communications, Vol. 29, No. 2, pp. 276–289, Feb 2011.
  5. “On The Primary Exclusive Regions in Cognitive Networks,
    M. Vu, N. Devroye, and V. Tarokh, IEEE Trans. on Wireless Comm., Vol. 8, No. 7, pp. 3380 – 3385, July 2009.
  6. “Capacity Impact of Location-aware Cognitive Sensing,
    P. Jia, M. Vu and T. Le-Ngoc, IEEE Conf. on Global Comm. (Globecom), Dec 2009.
  7. “Location-aware Cognitive Sensing for Maximizing Network Capacity,
    P. Jia, M. Vu and T. Le-Ngoc, Asilomar Conf. on Signals, Systems, and Computers, Nov 2009.
  8. “Cognitive Networks Achieve Throughput Scaling of a Homogeneous Network”,
    S-W. Jeon, N. Devroye, M. Vu, S-Y. Chung, V. Tarokh, Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), June 2009.
  9. “Cognitive radio: From theory to practical network engineering,
    E. Hossain, Long B. Le, N. Devroye, M. Vu, invited chapter in Advances in Wireless Communications, (Eds. V. Tarokh and I. Blake), Springer, 2009.
  10. “Cognitive Radio Networks: Information Theory Limits, Models and Design,
    N. Devroye, M. Vu, and V. Tarokh, IEEE Signal Proc. Magazine, Special Issue on Cognitive Radios, pp. 12-23, Nov. 2008.
  11. “An Overview of Scaling Laws in Ad Hoc and Cognitive Radio Networks,
    M. Vu, N. Devroye, and V. Tarokh, invited paper, Springer Journal, Special Issue on Cognitive Radio Technologies,  DOI: 10.1007/s11277-008-9479-0, Mar 2008.
  12. “Achievable Rates and Scaling Laws for Cognitive Radio Models”,
    N. Devroye, M. Vu, and V. Tarokh, invited paper, EURASIP JWCN Issue on Cognitive Radio and Dynamic Spectrum Sharing Systems, vol. 2008, Article ID 896246, Doi:10.11552008896246, 12 pages, Jan 2008.
  13. “Cognitive Sensing Based on Side Information,
    S-C Hong, M. Vu, and V. Tarokh, the Sarnoff Conf., Apr 2008.
  14. “Interference in a Cognitive Network with Beacon,
    M. Vu, S. Ghassemzadeh, and V. Tarokh, IEEE Wireless Comm. and Networking Conf. (WCNC), Mar 2008.
  15. “The Primary Exclusive Region in Cognitive Networks,
    M. Vu, N. Devroye, M. Sharif, and V. Tarokh, invited paper, IEEE Consumer Comm. and Networking Conf. (CCNC), Jan 2008.
  16. “Scaling Laws of Cognitive Networks,
    M. Vu, N. Devroye, M. Sharif, and V. Tarokh, invited paper, Int’l Conf. on Cognitive Radio Oriented Wireless Networks and Communications (Crowncom), Orlando, Aug 2007.

Interference Channel

  1. “Interfering Relay Channels,”
    H.T. Do, T.J. Oechtering, M. Skoglund, M. and M. Vu, “Interfering Relay Channels,” in Entropy 2017, vol. 19, no. 9, 40 pages, Sep. 2017.
  2. Analysis of Encoding and Decoding Techniques for the Interference Channel with Destination Cooperation,
    A. Abu Al Haija and M. Vu, 47th Annual Conference on Information Sciences and Systems (CISS), Mar 2013.
  3. Gaussian Interfering Relay Channels,”
    H. Do, T. Oechtering, M. Skoglund and M. Vu, 47th Asilomar Conf. on Signals, Systems, and Computers, Nov 2013. 
  4. Capacity Region of a Class of Interfering Relay Channels,”
    H. Do, T. Oechtering, M. Skoglund and M. Vu, 47th Asilomar Conf. on Signals, Systems, and Computers, Nov 2013.

MIMO Capacity

  1. Iterative Mode-Dropping for the Sum Capacity of MIMO-MAC with Per-Antenna Power Constraint,”
    Y. Zhu and M. Vu, IEEE Trans. on Comm., vol. 60, no. 9, pp. 2421 – 2426, Sept. 2012.
  2. “The Capacity of MIMO Channels with Per-Antenna Power Constraint,”[pdf]
    M. Vu, submitted to IEEE Transactions on Information Theory, Jun 2011.
  3. “MIMO Capacity with Per-antenna Power Constraint,” [pdf]
    M. Vu, IEEE Conf. on Global Comm. (Globecom), pp. 1-5 , Dec 2011.
  4. “MISO Capacity with Per-antenna Power Constraint,” [pdf] [arxiv]
    M. Vu, IEEE Trans. on Communications (transactions letter), Vol. 59, No. 5, pp. 1268-1274, May 2011.
  5. “On the Capacity of MIMO Wireless Channels with Dynamic,” [pdf]
    M. Vu and A. Paulraj, IEEE Journal on Selected Areas in Communications, Vol. 25, No. 7, pp. 1269-1283 , Sept 2007.
    Special Issue on Optimization of MIMO Transceivers for Realistic Communication Networks.
  6. “Capacity Optimization for Rician Correlated MIMO Wireless Channels,” [pdf]
    M. Vu and A. Paulraj, in Proc. 39th Asilomar Conf. on Signals, Systems, and Computers, pp. 133-138, Nov 2005.
  7. “Characterizing the Capacity for MIMO Wireless Channels with Non-zero Mean and Transmit Covariance,” [pdf]
    M. Vu and A. Paulraj, in Proc. 43rd Annual Allerton Conference on Communication, Control, and Computing, Sept 2005.
  8. “Some Asymptotic Capacity Results for MIMO Wireless with and without Channel Knowledge at the Transmitter,” [pdf]
    M. Vu and A. Paulraj, in Proc. 37th Asilomar Conf. on Signals, Systems, and Computers, pp. 258-262, Nov 2003.

Wireless Positioning

  1. “Device-Agnostic Wi-Fi Fingerprint Positioning for Consumer Applications,”
    B. Fischler, D. Griffin, T. Lubeck, K. H. Wapman, and M. Vu, IEEE Int’l Symposium on Personal, Indoor and Mobile Radio Commun. (PIMRC), 2015.

Miscellaneous

  1. Improving fNIRS-based BCIs with Convex Optimization for Generalized Classification and Semi-Supervised Learning,”
    H. Ethan, L. Wang, M. Vu, and R. J.K. Jacob, The Third Neuroadaptive Technology Conference, NAT’22, Germany, Oct. 2022.
  2. PLAN: A leafcutter ant colony optimization algorithm for ride-hailing services,”
    A. Anoushka and M.Vu, in Proc. of the Genetic and Evolutionary Computation Conference, pp. 4-12. Boston, 2022.