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Haris Vikalo
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2020 – today
- 2024
- [j56]Mónica Ribero, Haris Vikalo
:
Reducing communication in federated learning via efficient client sampling. Pattern Recognit. 148: 110122 (2024) - [c101]Yiyue Chen, Haris Vikalo, Chianing Wang:
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity. AAAI 2024: 11443-11452 - [c100]Hasan Burhan Beytur, Ahmet Gunhan Aydin, Gustavo de Veciana, Haris Vikalo:
Optimization of Offloading Policies for Accuracy-Delay Tradeoffs in Hierarchical Inference. INFOCOM 2024: 1989-1998 - [i36]Huancheng Chen, Haris Vikalo:
Recovering Labels from Local Updates in Federated Learning. CoRR abs/2405.00955 (2024) - 2023
- [j55]Ziqi Ke
, Haris Vikalo
:
Graph-Based Reconstruction and Analysis of Disease Transmission Networks Using Viral Genomic Data. J. Comput. Biol. 30(7): 796-813 (2023) - [j54]Mónica Ribero
, Haris Vikalo
, Gustavo de Veciana
:
Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints. IEEE J. Sel. Top. Signal Process. 17(1): 98-111 (2023) - [c99]Huancheng Chen, Haris Vikalo
:
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data. CVPR Workshops 2023: 5027-5036 - [c98]Yiyue Chen, Abolfazl Hashemi, Haris Vikalo
:
Accelerated Distributed Stochastic Non-Convex Optimization over Time-Varying Directed Networks. ICASSP 2023: 1-5 - [c97]Huancheng Chen, Chianing Wang, Haris Vikalo:
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation. ICLR 2023 - [i35]Huancheng Chen, Chianing Johnny Wang, Haris Vikalo:
The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation. CoRR abs/2301.08968 (2023) - [i34]Madhumitha Sakthi, Ahmed H. Tewfik, Marius Arvinte, Haris Vikalo:
Automotive RADAR sub-sampling via object detection networks: Leveraging prior signal information. CoRR abs/2302.10450 (2023) - [i33]Shorya Consul, John Robertson, Haris Vikalo:
XVir: A Transformer-Based Architecture for Identifying Viral Reads from Cancer Samples. CoRR abs/2308.14769 (2023) - [i32]Huancheng Chen, Haris Vikalo:
Accelerating Non-IID Federated Learning via Heterogeneity-Guided Client Sampling. CoRR abs/2310.00198 (2023) - [i31]Huancheng Chen, Haris Vikalo:
Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices. CoRR abs/2311.18129 (2023) - [i30]Yiyue Chen, Haris Vikalo, Chianing Johnny Wang:
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity. CoRR abs/2312.13380 (2023) - 2022
- [j53]Mónica Ribero
, Jette Henderson
, Sinead Williamson
, Haris Vikalo
:
Federating recommendations using differentially private prototypes. Pattern Recognit. 129: 108746 (2022) - [j52]Abolfazl Hashemi
, Rasoul Shafipour, Haris Vikalo
, Gonzalo Mateos
:
Towards accelerated greedy sampling and reconstruction of bandlimited graph signals. Signal Process. 195: 108505 (2022) - [j51]Yiyue Chen
, Abolfazl Hashemi
, Haris Vikalo
:
Communication-Efficient Variance-Reduced Decentralized Stochastic Optimization Over Time-Varying Directed Graphs. IEEE Trans. Autom. Control. 67(12): 6583-6594 (2022) - [j50]Abolfazl Hashemi
, Anish Acharya
, Rudrajit Das
, Haris Vikalo
, Sujay Sanghavi, Inderjit S. Dhillon:
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Federated Learning. IEEE Trans. Parallel Distributed Syst. 33(11): 2727-2739 (2022) - [j49]Abolfazl Hashemi
, Haris Vikalo
, Gustavo de Veciana
:
On the Benefits of Progressively Increasing Sampling Sizes in Stochastic Greedy Weak Submodular Maximization. IEEE Trans. Signal Process. 70: 3978-3992 (2022) - [j48]Ziqi Ke
, Haris Vikalo
:
Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder. IEEE Trans. Wirel. Commun. 21(1): 370-382 (2022) - [c96]Sameer Bibikar, Haris Vikalo
, Zhangyang Wang, Xiaohan Chen:
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better. AAAI 2022: 6080-6088 - [c95]Ziqi Ke
, Haris Vikalo
:
Deep learning for assembly of haplotypes and viral quasispecies from short and long sequencing reads. BCB 2022: 3:1-3:10 - [c94]Madhumitha Sakthi, Ahmed H. Tewfik, Marius Arvinte, Haris Vikalo:
End-to-end system for object detection from sub-sampled radar data. EUSIPCO 2022: 1886-1890 - [i29]Madhumitha Sakthi, Ahmed H. Tewfik, Marius Arvinte, Haris Vikalo:
End-to-end system for object detection from sub-sampled radar data. CoRR abs/2203.03905 (2022) - [i28]Mónica Ribero, Haris Vikalo, Gustavo de Veciana:
Federated Learning Under Intermittent Client Availability and Time-Varying Communication Constraints. CoRR abs/2205.06730 (2022) - [i27]Huancheng Chen, Haris Vikalo:
Federated Learning in Non-IID Settings Aided by Differentially Private Synthetic Data. CoRR abs/2206.00686 (2022) - 2021
- [j47]Abolfazl Hashemi
, Mahsa Ghasemi
, Haris Vikalo
, Ufuk Topcu
:
Randomized Greedy Sensor Selection: Leveraging Weak Submodularity. IEEE Trans. Autom. Control. 66(1): 199-212 (2021) - [j46]Natalia M. Arzeno
, Haris Vikalo
:
Evolutionary Clustering via Message Passing. IEEE Trans. Knowl. Data Eng. 33(6): 2452-2466 (2021) - [c93]Mahsa Ghasemi, Abolfazl Hashemi, Haris Vikalo
, Ufuk Topcu:
Online Learning with Implicit Exploration in Episodic Markov Decision Processes. ACC 2021: 1953-1958 - [c92]Abolfazl Hashemi, Haris Vikalo
, Gustavo de Veciana:
On the Performance-Complexity Tradeoff in Stochastic Greedy Weak Submodular Optimization. ICASSP 2021: 3540-3544 - [c91]Yiyue Chen, Abolfazl Hashemi, Haris Vikalo
:
Decentralized Optimization on Time-Varying Directed Graphs Under Communication Constraints. ICASSP 2021: 3670-3674 - [c90]Ziqi Ke
, Haris Vikalo
:
Real-Time Radio Modulation Classification With An LSTM Auto-Encoder. ICASSP 2021: 4935-4939 - [c89]Michael Stecklein, Hasan Burhan Beytur, Gustavo de Veciana, Haris Vikalo
:
Optimizing Resource Constrained Distributed Collaborative Sensing. ICC Workshops 2021: 1-6 - [c88]Shorya Consul, Hasan Burhan Beytur, Gustavo de Veciana, Haris Vikalo
:
RF-based Network Inference: Theoretical Foundations. MILCOM 2021: 291-296 - [c87]Sangsu Lee, Xi Zheng
, Jie Hua, Haris Vikalo
, Christine Julien
:
Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications. PerCom 2021: 1-8 - [c86]Sangsu Lee, Xi Zheng
, Jie Hua, Haris Vikalo
, Christine Julien:
Artifact: Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications. PerCom Workshops 2021: 438-439 - [c85]Mahsa Ghasemi, Abolfazl Hashemi, Haris Vikalo, Ufuk Topcu:
No-regret learning with high-probability in adversarial Markov decision processes. UAI 2021: 992-1001 - [i26]Yiyue Chen, Abolfazl Hashemi, Haris Vikalo:
Communication-Efficient Variance-Reduced Decentralized Stochastic Optimization over Time-Varying Directed Graphs. CoRR abs/2101.09583 (2021) - [i25]Sangsu Lee, Xi Zheng, Jie Hua, Haris Vikalo, Christine Julien:
Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications. CoRR abs/2103.13266 (2021) - [i24]Sameer Bibikar, Haris Vikalo, Zhangyang Wang, Xiaohan Chen:
Federated Dynamic Sparse Training: Computing Less, Communicating Less, Yet Learning Better. CoRR abs/2112.09824 (2021) - 2020
- [c84]Ziqi Ke
, Haris Vikalo
:
A Graph Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction. AAAI 2020: 719-726 - [c83]Mahsa Ghasemi, Abolfazl Hashemi, Haris Vikalo
, Ufuk Topcu
:
Identifying Sparse Low-Dimensional Structures in Markov Chains: A Nonnegative Matrix Factorization Approach. ACC 2020: 1093-1098 - [c82]Ziqi Ke, Haris Vikalo:
A Convolutional Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction. NeurIPS 2020 - [c81]Muhammad Usman, Wenxi Wang, Marko Vasic, Kaiyuan Wang, Haris Vikalo
, Sarfraz Khurshid:
A study of the learnability of relational properties: model counting meets machine learning (MCML). PLDI 2020: 1098-1111 - [i23]Mónica Ribero, Jette Henderson, Sinead Williamson, Haris Vikalo:
Federating Recommendations Using Differentially Private Prototypes. CoRR abs/2003.00602 (2020) - [i22]Yiyue Chen, Abolfazl Hashemi, Haris Vikalo:
Communication-Efficient Algorithms for Decentralized Optimization Over Directed Graphs. CoRR abs/2005.13189 (2020) - [i21]Mónica Ribero, Haris Vikalo:
Communication-Efficient Federated Learning via Optimal Client Sampling. CoRR abs/2007.15197 (2020) - [i20]Ziqi Ke, Haris Vikalo:
Real-Time Radio Technology and Modulation Classification via an LSTM Auto-Encoder. CoRR abs/2011.08295 (2020) - [i19]Abolfazl Hashemi, Anish Acharya, Rudrajit Das, Haris Vikalo, Sujay Sanghavi, Inderjit S. Dhillon:
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization. CoRR abs/2011.10643 (2020)
2010 – 2019
- 2019
- [j45]Somsubhra Barik
, Haris Vikalo
:
Matrix Completion and Performance Guarantees for Single Individual Haplotyping. IEEE Trans. Signal Process. 67(18): 4782-4794 (2019) - [c80]Mahsa Ghasemi, Abolfazl Hashemi, Ufuk Topcu
, Haris Vikalo
:
On Submodularity of Quadratic Observation Selection in Constrained Networked Sensing Systems. ACC 2019: 4671-4676 - [c79]Shorya Consul, Haris Vikalo
:
Reconstructing Intra-Tumor Heterogeneity via Convex Optimization and Branch-and-Bound Search. BCB 2019: 524-529 - [c78]Sara Mourad, Haris Vikalo
, Ahmed H. Tewfik:
Online selective training for faster neural network learning. DSW 2019: 135-139 - [c77]Rasoul Shafipour, Abolfazl Hashemi, Gonzalo Mateos
, Haris Vikalo
:
Online Topology Inference from Streaming Stationary Graph Signals. DSW 2019: 140-144 - [c76]Sara Mourad, Ahmed H. Tewfik, Haris Vikalo
:
Weighted Subset Selection for Fast SVM Training. EUSIPCO 2019: 1-5 - [c75]Abolfazl Hashemi, Haris Vikalo
:
Evolutionary Subspace Clustering: Discovering Structure in Self-expressive Time-series Data. ICASSP 2019: 3707-3711 - [c74]Mónica Ribero, Robert W. Heath Jr.
, Haris Vikalo
, Dmitry Chizhik, Reinaldo A. Valenzuela:
Deep Learning Propagation Models over Irregular Terrain. ICASSP 2019: 4519-4523 - [c73]Shorya Consul, Abolfazl Hashemi, Haris Vikalo
:
A Map Framework for Support Recovery of Sparse Signals Using Orthogonal Least Squares. ICASSP 2019: 5127-5131 - [c72]Abolfazl Hashemi, Mahsa Ghasemi, Haris Vikalo, Ufuk Topcu:
Submodular Observation Selection and Information Gathering for Quadratic Models. ICML 2019: 2653-2662 - [i18]Gustavo de Veciana, Abolfazl Hashemi, Haris Vikalo:
Stochastic-Greedy++: Closing the Optimality Gap in Exact Weak Submodular Maximization. CoRR abs/1907.09064 (2019) - [i17]Mahsa Ghasemi, Abolfazl Hashemi, Haris Vikalo, Ufuk Topcu:
Identifying Low-Dimensional Structures in Markov Chains: A Nonnegative Matrix Factorization Approach. CoRR abs/1909.12898 (2019) - [i16]Ziqi Ke, Haris Vikalo:
A Graph Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction. CoRR abs/1911.05316 (2019) - [i15]Abishek Sankararaman, Haris Vikalo, François Baccelli:
ComHapDet: A Spatial Community Detection Algorithm for Haplotype Assembly. CoRR abs/1911.12285 (2019) - [i14]Muhammad Usman, Wenxi Wang, Kaiyuan Wang, Marko Vasic, Haris Vikalo, Sarfraz Khurshid:
A Study of the Learnability of Relational Properties (Model Counting Meets Machine Learning). CoRR abs/1912.11580 (2019) - [i13]Natalia M. Arzeno, Haris Vikalo:
Evolutionary Clustering via Message Passing. CoRR abs/1912.11970 (2019) - 2018
- [j44]Soyeon Ahn, Ziqi Ke
, Haris Vikalo:
Viral quasispecies reconstruction via tensor factorization with successive read removal. Bioinform. 34(13): i23-i31 (2018) - [j43]Abolfazl Hashemi
, Haris Vikalo
:
Accelerated orthogonal least-squares for large-scale sparse reconstruction. Digit. Signal Process. 82: 91-105 (2018) - [j42]Soyeon Ahn, Haris Vikalo:
aBayesQR: A Bayesian Method for Reconstruction of Viral Populations Characterized by Low Diversity. J. Comput. Biol. 25(7): 637-648 (2018) - [j41]Abolfazl Hashemi
, Haris Vikalo
:
Evolutionary Self-Expressive Models for Subspace Clustering. IEEE J. Sel. Top. Signal Process. 12(6): 1534-1546 (2018) - [j40]Heeseong Yang, Joohwan Chun, Haris Vikalo:
Cyclic block coordinate minimization algorithms for DOA estimation in co-prime arrays. Signal Process. 145: 272-284 (2018) - [c71]Abolfazl Hashemi, Mahsa Ghasemi, Haris Vikalo, Ufuk Topcu
:
A Randomized Greedy Algorithm for Near-Optimal Sensor Scheduling in Large-Scale Sensor Networks. ACC 2018: 1027-1032 - [c70]Abolfazl Hashemi, Osman Fatih Kiliç, Haris Vikalo
:
Near-Optimal Distributed Estimation for a Network of Sensing Units Operating Under Communication Constraints. CDC 2018: 2890-2895 - [c69]Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo
, Gonzalo Mateos:
A Novel Scheme for Support Identification and Iterative Sampling of Bandlimited Graph Signals. GlobalSIP 2018: 778-782 - [c68]Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo, Gonzalo Mateos:
Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation. ICASSP 2018: 4179-4183 - [i12]Somsubhra Barik, Haris Vikalo:
Matrix Completion and Performance Guarantees for Single Individual Haplotyping. CoRR abs/1806.08647 (2018) - [i11]Abolfazl Hashemi, Haris Vikalo:
Evolutionary Self-Expressive Models for Subspace Clustering. CoRR abs/1810.11957 (2018) - 2017
- [j39]Hongbo Si
, Haris Vikalo, Sriram Vishwanath:
Information-Theoretic Analysis of Haplotype Assembly. IEEE Trans. Inf. Theory 63(6): 3468-3479 (2017) - [j38]Shreepriya Das, Haris Vikalo
:
Optimal Haplotype Assembly via a Branch-and-Bound Algorithm. IEEE Trans. Mol. Biol. Multi Scale Commun. 3(1): 1-12 (2017) - [c67]Soyeon Ahn, Ziqi Ke
, Haris Vikalo:
Viral quasispecies reconstruction via tensor factorization. Allerton 2017: 1236-1239 - [c66]Abolfazl Hashemi, Banghua Zhu, Haris Vikalo:
Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids. BCB 2017: 764-765 - [c65]Xinnian Zheng, Haris Vikalo, Shuang Song, Lizy K. John, Andreas Gerstlauer:
Sampling-based binary-level cross-platform performance estimation. DATE 2017: 1709-1714 - [c64]Sara Mourad, Ahmed H. Tewfik, Haris Vikalo:
Data subset selection for efficient SVM training. EUSIPCO 2017: 833-837 - [c63]Natalia M. Arzeno, Haris Vikalo:
Evolutionary affinity propagation. ICASSP 2017: 2681-2685 - [c62]Somsubhra Barik, Haris Vikalo:
Binary matrix completion with performance guarantees for single individual haplotyping. ICASSP 2017: 2716-2720 - [c61]Abolfazl Hashemi, Haris Vikalo:
Recovery of sparse signals via Branch and Bound Least-Squares. ICASSP 2017: 4760-4764 - [c60]Soyeon Ahn, Haris Vikalo:
aBayesQR: A Bayesian Method for Reconstruction of Viral Populations Characterized by Low Diversity. RECOMB 2017: 353-369 - [i10]Abolfazl Hashemi, Mahsa Ghasemi, Haris Vikalo, Ufuk Topcu:
A Randomized Greedy Algorithm for Near-Optimal Sensor Scheduling in Large-Scale Sensor Networks. CoRR abs/1709.08823 (2017) - [i9]Abolfazl Hashemi, Haris Vikalo:
Accelerated Sparse Subspace Clustering. CoRR abs/1711.00126 (2017) - [i8]Abolfazl Hashemi, Rasoul Shafipour, Haris Vikalo, Gonzalo Mateos
:
Sampling and Reconstruction of Graph Signals via Weak Submodularity and Semidefinite Relaxation. CoRR abs/1711.00142 (2017) - 2016
- [j37]Eliza O'Reilly, François Baccelli, Gustavo de Veciana, Haris Vikalo:
End-to-End Optimization of High-Throughput DNA Sequencing. J. Comput. Biol. 23(10): 789-800 (2016) - [j36]Changxiao Cai, Sujay Sanghavi, Haris Vikalo
:
Structured Low-Rank Matrix Factorization for Haplotype Assembly. IEEE J. Sel. Top. Signal Process. 10(4): 647-657 (2016) - [j35]Zrinka Puljiz, Haris Vikalo:
Decoding Genetic Variations: Communications-Inspired Haplotype Assembly. IEEE ACM Trans. Comput. Biol. Bioinform. 13(3): 518-530 (2016) - [c59]Vutha Va
, Haris Vikalo, Robert W. Heath Jr.
:
Beam tracking for mobile millimeter wave communication systems. GlobalSIP 2016: 743-747 - [c58]Abolfazl Hashemi, Haris Vikalo:
Sparse linear regression via generalized orthogonal least-squares. GlobalSIP 2016: 1305-1309 - [c57]Heeseong Yang, Joohwan Chun, Haris Vikalo:
Nonnegative gridless compressive sensing for co-prime arrays. GlobalSIP 2016: 1364-1367 - [c56]Changxiao Cai, Sujay Sanghavi, Haris Vikalo:
Structurally-constrained gradient descent for matrix factorization in haplotype assembly problems. ICASSP 2016: 2638-2641 - [i7]Abolfazl Hashemi, Haris Vikalo:
Sparse Linear Regression via Generalized Orthogonal Least-Squares. CoRR abs/1602.06916 (2016) - [i6]Abolfazl Hashemi, Haris Vikalo:
Sampling Requirements and Accelerated Schemes for Sparse Linear Regression with Orthogonal Least-Squares. CoRR abs/1608.02549 (2016) - [i5]Abolfazl Hashemi, Haris Vikalo:
Sparse recovery via Orthogonal Least-Squares under presence of Noise. CoRR abs/1608.02554 (2016) - 2015
- [j34]Soyeon Ahn, Haris Vikalo:
Joint haplotype assembly and genotype calling via sequential Monte Carlo algorithm. BMC Bioinform. 16: 223:1-223:10 (2015) - [j33]Natalia M. Arzeno, Karla A. Lawson
, Sarah V. Duzinski, Haris Vikalo:
Designing optimal mortality risk prediction scores that preserve clinical knowledge. J. Biomed. Informatics 56: 145-156 (2015) - [j32]Natalia M. Arzeno, Haris Vikalo:
Semi-Supervised Affinity Propagation with Soft Instance-Level Constraints. IEEE Trans. Pattern Anal. Mach. Intell. 37(5): 1041-1052 (2015) - [c55]Todd Richard Goodall, Alan C. Bovik, Haris Vikalo, Nicholas G. Paulter Jr.:
Non-uniformity correction of IR images using natural scene statistics. GlobalSIP 2015: 230-234 - [c54]Abhishek K. Gupta
, Somsubhra Barik, Haris Vikalo:
Distributed self localization of sensors with poisson deployment using extended Kalman filter. WCNC 2015: 1500-1505 - [i4]Jeffrey G. Andrews, Alexandros G. Dimakis, Lara Dolecek, Michelle Effros, Muriel Médard, Olgica Milenkovic, Andrea Montanari, Sriram Vishwanath, Edmund M. Yeh, Randall Berry, Ken R. Duffy, Soheil Feizi, Saul Kato, Manolis Kellis, Stuart Licht, Jon Sorenson, Lav R. Varshney, Haris Vikalo:
A Perspective on Future Research Directions in Information Theory. CoRR abs/1507.05941 (2015) - 2014
- [j31]Somsubhra Barik, Haris Vikalo:
Sparsity-Aware Sphere Decoding: Algorithms and Complexity Analysis. IEEE Trans. Signal Process. 62(9): 2212-2225 (2014) - [j30]Xiaohu Shen, Manohar Shamaiah, Haris Vikalo:
Iterative Learning for Reference-Guided DNA Sequence Assembly From Short Reads: Algorithms and Limits of Performance. IEEE Trans. Signal Process. 62(17): 4425-4435 (2014) - [c53]Shreepriya Das, Haris Vikalo:
Optimal haplotype assembly with statistical pruning. GlobalSIP 2014: 1330-1333 - [c52]Zrinka Puljiz, Haris Vikalo:
Iterative learning of single individual haplotypes from high-throughput DNA sequencing data. ISTC 2014: 147-151 - [c51]Hongbo Si, Haris Vikalo, Sriram Vishwanath:
Haplotype assembly: An information theoretic view. ITW 2014: 182-186 - [i3]Somsubhra Barik, Haris Vikalo:
Sparsity-aware sphere decoding: Algorithms and complexity analysis. CoRR abs/1402.1519 (2014) - [i2]Xiaohu Shen, Manohar Shamaiah, Haris Vikalo:
Iterative Learning for Reference-Guided DNA Sequence Assembly from Short Reads: Algorithms and Limits of Performance. CoRR abs/1403.5686 (2014) - [i1]Hongbo Si, Haris Vikalo, Sriram Vishwanath:
Haplotype Assembly: An Information Theoretic View. CoRR abs/1404.0097 (2014) - 2013
- [j29]Shreepriya Das, Haris Vikalo:
Base calling for high-throughput short-read sequencing: dynamic programming solutions. BMC Bioinform. 14: 129 (2013) - [j28]Sang Hyun Lee, Manohar Shamaiah, Haris Vikalo, Sriram Vishwanath:
Message-Passing Algorithms for Coordinated Spectrum Sensing in Cognitive Radio Networks. IEEE Commun. Lett. 17(4): 812-815 (2013) - [j27]Mijung Park, Marcel Nassar, Haris Vikalo:
Bayesian Active Learning for Drug Combinations. IEEE Trans. Biomed. Eng. 60(11): 3248-3255 (2013) - [c50]Zrinka Puljiz, Haris Vikalo:
A message passing algorithm for haplotype assembly. ACSSC 2013: 1726-1729 - [c49]Soyeon Ahn, Haris Vikalo:
Deterministic sequential Monte Carlo for haplotype inference. GlobalSIP 2013: 64 - [c48]Somsubhra Barik, Haris Vikalo:
Expected complexity of sphere decoding for sparse integer least-square problems. ICASSP 2013: 4668-4672 - [c47]Xiaohu Shen, Manohar Shamaiah, Haris Vikalo:
Message passing algorithm for inferring consensus sequence from next-generation sequencing data. ISIT 2013: 1631-1634 - 2012
- [j26]Shreepriya Das, Haris Vikalo:
OnlineCall: fast online parameter estimation and base calling for illumina's next-generation sequencing. Bioinform. 28(13): 1677-1683 (2012) - [j25]Xiaohu Shen, Haris Vikalo:
ParticleCall: A particle filter for base calling in next-generation sequencing systems. BMC Bioinform. 13: 160 (2012) - [j24]Manohar Shamaiah, Sang Hyun Lee, Sriram Vishwanath, Haris Vikalo:
Distributed Algorithms for Spectrum Access in Cognitive Radio Relay Networks. IEEE J. Sel. Areas Commun. 30(10): 1947-1957 (2012) - [j23]Manohar Shamaiah, Sang Hyun Lee, Haris Vikalo:
Graphical Models and Inference on Graphs in Genomics: Challenges of high-throughput data analysis. IEEE Signal Process. Mag. 29(1): 51-65 (2012) - [j22]Manohar Shamaiah, Xiaohu Shen, Haris Vikalo:
Estimating Parameters of Sampled Diffusion Processes in Affinity Biosensors. IEEE Trans. Signal Process. 60(6): 3228-3239 (2012) - [j21]Ting Wu, Haris Vikalo:
Joint Parameter Estimation and Base-Calling for Pyrosequencing Systems. IEEE Trans. Signal Process. 60(8): 4376-4386 (2012) - [j20]Manohar Shamaiah, Siddhartha Banerjee, Haris Vikalo:
Greedy Sensor Selection under Channel Uncertainty. IEEE Wirel. Commun. Lett. 1(4): 376-379 (2012) - [c46]Xiaohu Shen, Haris Vikalo:
A message passing algorithm for reference-guided sequence assembly from high-throughput sequencing data. GENSiPS 2012: 35-37 - [c45]Manohar Shamaiah, Haris Vikalo:
Base calling error rates in next-generation DNA sequencing. SSP 2012: 692-695 - [c44]Mijung Park, Marcel Nassar, Brian L. Evans, Haris Vikalo:
Adaptive experimental design for drug combinations. SSP 2012: 712-715 - 2011
- [j19]Manohar Shamaiah, Haris Vikalo:
Estimating Time-Varying Sparse Signals Under Communication Constraints. IEEE Trans. Signal Process. 59(6): 2961-2964 (2011) - [c43]Ting Wu, Haris Vikalo, Manohar Shamaiah:
An MCMC algorithm for base calling in sequencing-by-synthesis. ACSCC 2011: 1017-1020 - [c42]Sang Hyun Lee, Manohar Shamaiah, Sriram Vishwanath, Haris Vikalo:
A message-passing algorithm for spectrum access in cognitive radio relay networks. ACSCC 2011: 1753-1757 - [c41]Shreepriya Das, Haris Vikalo:
Base-calling for Illumina's next-generation DNA sequencing systems via Viterbi algorithm. Allerton 2011: 1733-1736 - [c40]Manohar Shamaiah, Haris Vikalo:
A dual Kalman filter for parameter-state estimation in real-time DNA microarrays. EMBC 2011: 7614-7617 - [c39]Xiaohu Shen, Haris Vikalo:
A sequential Monte Carlo base-calling method for next-generation dna sequencing. GENSiPS 2011: 121-122 - [c38]Manohar Shamaiah, Xiaohu Shen, Haris Vikalo:
Sequential Monte Carlo method for parameter estimation in diffusion models of affinity-based biosensors. ICASSP 2011: 525-528 - [c37]Sang Hyun Lee, Manohar Shamaiah, Haris Vikalo:
Message-passing for base-calling in sequencing-by-synthesis systems. ICASSP 2011: 777-780 - [c36]Manohar Shamaiah, Sang Hyun Lee, Sriram Vishwanath, Haris Vikalo:
Distributed routing in networks using affinity propagation. ICASSP 2011: 3036-3039 - 2010
- [j18]Xiaohu Shen, Haris Vikalo:
Inferring Parameters of Gene Regulatory Networks via Particle Filtering. EURASIP J. Adv. Signal Process. 2010 (2010) - [j17]Haris Vikalo, Mahsuni Gokdemir:
An MCMC Algorithm for Target Estimation in Real-Time DNA Microarrays. EURASIP J. Adv. Signal Process. 2010 (2010) - [j16]Haris Vikalo, Babak Hassibi, Arjang Hassibi:
Limits of performance of quantitative polymerase chain reaction systems. IEEE Trans. Inf. Theory 56(2): 688-695 (2010) - [c35]Manohar Shamaiah, Siddhartha Banerjee, Haris Vikalo:
Greedy sensor selection: Leveraging submodularity. CDC 2010: 2572-2577 - [c34]Shreepriya Das, Haris Vikalo, Arjang Hassibi:
Model-based sequential base calling for Illumina sequencing. GENSiPS 2010: 1-4 - [c33]Manohar Shamaiah, Sang Hyun Lee, Haris Vikalo:
Inference of gene-regulatory networks using message-passing algorithms. GENSiPS 2010: 1-4 - [c32]Sang Hyun Lee, Haris Vikalo, Sriram Vishwanath:
Further results on message-passing algorithms for motif finding. ICASSP 2010: 534-537 - [c31]Xiaohu Shen, Haris Vikalo:
Inferring parameters of gene regulatory networks via particle filtering. ICASSP 2010: 546-549 - [c30]Ting Wu, Haris Vikalo:
Maximum likelihood DNA sequence detection via sphere decoding. ICASSP 2010: 586-589 - [c29]Manohar Shamaiah, Haris Vikalo:
Rao-Blackwellized unscented Kalman filter for nonlinear systems with bandwidth constraints. ICASSP 2010: 2642-2645
2000 – 2009
- 2009
- [j15]Mostafa El-Khamy
, Haris Vikalo, Babak Hassibi, Robert J. McEliece:
Performance of sphere decoding of block codes. IEEE Trans. Commun. 57(10): 2940-2950 (2009) - [c28]Haris Vikalo, Babak Hassibi:
Limits of performance of real-time DNA microarrays. Allerton 2009: 678-683 - [c27]Shreepriya Das, Haris Vikalo, Arjang Hassibi:
Stochastic modeling of reaction kinetics in biosensors using the Fokker Planck equation. GENSiPS 2009: 1-4 - [c26]Mahsuni Gokdemir, Haris Vikalo:
A particle filtering algorithm for parameter estimation in real-time biosensor arrays. GENSiPS 2009: 1-4 - [c25]Sang Hyun Lee, Haris Vikalo, Sriram Vishwanath:
Message-passing for motif finding. GENSiPS 2009: 1-4 - [c24]Arun Miduthuri, Ting Wu, Haris Vikalo:
Target estimation in real-time polymerase chain reaction using sequential Monte Carlo. GENSiPS 2009: 1-4 - 2008
- [j14]Farzad Parvaresh, Haris Vikalo
, Sidhant Misra, Babak Hassibi:
Recovering Sparse Signals Using Sparse Measurement Matrices in Compressed DNA Microarrays. IEEE J. Sel. Top. Signal Process. 2(3): 275-285 (2008) - [j13]Haris Vikalo, Babak Hassibi, Arjang Hassibi:
Modeling and Estimation for Real-Time Microarrays. IEEE J. Sel. Top. Signal Process. 2(3): 286-296 (2008) - [j12]Mihailo Stojnic, Haris Vikalo, Babak Hassibi:
Speeding up the Sphere Decoder With Hinfty and SDP Inspired Lower Bounds. IEEE Trans. Signal Process. 56(2): 712-726 (2008) - [c23]Haris Vikalo, Arjang Hassibi:
Estimation in real-time affinity-based biosensors. ACSCC 2008: 1919-1922 - [c22]Haris Vikalo, Babak Hassibi, Arjang Hassibi:
On estimation in real-time microarrays. ICASSP 2008: 577-580 - [c21]Haris Vikalo, Farzad Parvaresh, Sidhant Misra, Babak Hassibi:
Sparse measurements, compressed sampling, and DNA microarrays. ICASSP 2008: 581-584 - 2007
- [c20]Mihailo Stojnic, Babak Hassibi, Haris Vikalo:
PEP Analysis of the SDP Based Joint Channel Estimation and Signal Detection. ICASSP (3) 2007: 69-72 - [c19]Haris Vikalo, Babak Hassibi, Arjang Hassibi:
ML Estimation of DNA Initial Copy Number in Polymerase Chain Reaction (PCR) Processes. ICASSP (1) 2007: 417-420 - [c18]Mihailo Stojnic, Babak Hassibi, Haris Vikalo:
PEP analysis of SDP-based non-coherent signal detection. ISIT 2007: 2916-2920 - 2006
- [j11]Haris Vikalo, Babak Hassibi, Urbashi Mitra:
Sphere-Constrained ML Detection for Frequency-Selective Channels. IEEE Trans. Commun. 54(7): 1179-1183 (2006) - [j10]Haris Vikalo, Babak Hassibi, Arjang Hassibi:
A statistical model for microarrays, optimal estimation algorithms, and limits of performance. IEEE Trans. Signal Process. 54(6-2): 2444-2455 (2006) - [j9]Haris Vikalo, Babak Hassibi:
On joint detection and decoding of linear block codes on Gaussian vector channels. IEEE Trans. Signal Process. 54(9): 3330-3342 (2006) - [j8]Haris Vikalo, Babak Hassibi, Petre Stoica:
Efficient joint maximum-likelihood channel estimation and signal detection. IEEE Trans. Wirel. Commun. 5(7): 1838-1845 (2006) - [j7]Mihailo Stojnic, Haris Vikalo, Babak Hassibi:
Rate maximization in multi-antenna broadcast channels with linear preprocessing. IEEE Trans. Wirel. Commun. 5(9): 2338-2342 (2006) - [c17]Mihailo Stojnic, Haris Vikalo, Babak Hassibi:
Further Results on Speeding up the Sphere Decoder. ICASSP (4) 2006: 549-552 - [c16]Mihailo Stojnic, Haris Vikalo, Babak Hassibi:
Asymptotic Analysis of the Gaussian Broadcast Channel with Perturbation Preprocessing. ICASSP (4) 2006: 777-780 - [c15]Haris Vikalo, Babak Hassibi, Arjang Hassibi:
On Limits of Performance of Dna Microarrays. ICASSP (2) 2006: 1012-1015 - [c14]Mostafa El-Khamy
, Haris Vikalo, Babak Hassibi, Robert J. McEliece:
On the Performance of Sphere Decoding of Block Codes. ISIT 2006: 1964-1968 - 2005
- [j6]Haris Vikalo, Babak Hassibi, Alper T. Erdogan
, Thomas Kailath:
On robust signal reconstruction in noisy filter banks. Signal Process. 85(1): 1-14 (2005) - [j5]Babak Hassibi, Haris Vikalo:
On the sphere-decoding algorithm I. Expected complexity. IEEE Trans. Signal Process. 53(8-1): 2806-2818 (2005) - [j4]Haris Vikalo, Babak Hassibi:
On the sphere-decoding algorithm II. Generalizations, second-order statistics, and applications to communications. IEEE Trans. Signal Process. 53(8-1): 2819-2834 (2005) - [c13]Mihailo Stojnic, Haris Vikalo, Babak Hassibi:
A branch and bound approach to speed up the sphere decoder. ICASSP (3) 2005: 429-432 - [c12]Mostafa El-Khamy
, Haris Vikalo, Babak Hassibi:
Bounds on the performance of sphere decoding of linear block codes. ITW 2005: 47-51 - 2004
- [j3]Haris Vikalo, Babak Hassibi, Bertrand M. Hochwald, Thomas Kailath:
On the capacity of frequency- selective channels in training-based transmission schemes. IEEE Trans. Signal Process. 52(9): 2572-2583 (2004) - [j2]Haris Vikalo, Babak Hassibi, Thomas Kailath:
Iterative Decoding for MIMO Channels Via Modified Sphere Decoding. IEEE Trans. Wirel. Commun. 3(6): 2299-2311 (2004) - [c11]Mihailo Stojnic, Haris Vikalo, Babak Hassibi:
Rate maximization in multi-antenna broadcast channels with linear preprocessing. GLOBECOM 2004: 3957-3961 - [c10]Haris Vikalo, Babak Hassibi:
Statistical approach to ML decoding of linear block codes on symmetric channels. ISIT 2004: 522 - 2003
- [c9]Babak Hassibi, Haris Vikalo:
Maximum-likelihood decoding and integer least-squares: The expected complexity. Multiantenna Channels: Capacity, Coding and Signal Processing 2003: 161-191 - [c8]Haris Vikalo, Babak Hassibi, Urbashi Mitra:
Sphere-constrained ML detection for frequency-selective channels. ICASSP (4) 2003: 1-4 - [c7]Petre Stoica, Haris Vikalo, Babak Hassibi:
Joint maximum-likelihood channel estimation and signal detection for SIMO channels. ICASSP (4) 2003: 13-16 - 2002
- [j1]Haris Vikalo, Babak Hassibi:
Maximum-Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding. EURASIP J. Adv. Signal Process. 2002(5): 525-531 (2002) - [c6]Babak Hassibi, Haris Vikalo:
On the expected complexity of integer least-squares problems. ICASSP 2002: 1497-1500 - [c5]Haris Vikalo, Babak Hassibi:
Towards closing the capacity gap on multiple antenna channels. ICASSP 2002: 2385-2388 - 2001
- [c4]Haris Vikalo, Babak Hassibi, Bertrand M. Hochwald, Thomas Kailath:
Optimal training for frequency-selective fading channels. ICASSP 2001: 2105-2108 - 2000
- [c3]Haris Vikalo, Babak Hassibi, Thomas Kailath:
Mixed H2/H∞ optimal signal reconstruction in noisy filter banks. ICASSP 2000: 500-503 - [c2]Tajana Simunic, Haris Vikalo, Peter W. Glynn, Giovanni De Micheli:
Energy efficient design of portable wireless systems. ISLPED 2000: 49-54
1990 – 1999
- 1999
- [c1]Haris Vikalo, Babak Hassibi, Thomas Kailath:
On H∞ optimal signal reconstruction in noisy filter banks. ICASSP 1999: 1493-1496
Coauthor Index
![](https://dblp.org/img/cog.dark.24x24.png)
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