18 citations · 41 across the 12 of their papers we have counts for
18 papers
GUTS: Generalized Uncertainty-Aware Thompson Sampling for Multi-Agent Active Search
Nikhil Angad Bakshi, Tejus Gupta, Ramina Ghods +1
Robotic solutions for quick disaster response are essential to ensure minimal loss of life, especially when the search area is too dangerous or too vast for human rescuers. We mode…
Cost Aware Asynchronous Multi-Agent Active Search
Arundhati Banerjee, Ramina Ghods, Jeff Schneider
Multi-agent active search requires autonomous agents to choose sensing actions that efficiently locate targets. In a realistic setting, agents also must consider the costs that the…
Multi-Agent Active Search using Detection and Location Uncertainty
Arundhati Banerjee, Ramina Ghods, Jeff Schneider
Active search, in applications like environment monitoring or disaster response missions, involves autonomous agents detecting targets in a search space using decision making algor…
Multi-Agent Active Search using Realistic Depth-Aware Noise Model
Ramina Ghods, William J. Durkin, Jeff Schneider
The active search for objects of interest in an unknown environment has many robotics applications including search and rescue, detecting gas leaks or locating animal poachers. Exi…
Optimal Data Detection and Signal Estimation in Systems with Input Noise
Ramina Ghods, Charles Jeon, Arian Maleki +1
Practical systems often suffer from hardware impairments that already appear during signal generation. Despite the limiting effect of such input-noise impairments on signal process…
Asynchronous Multi Agent Active Search
Ramina Ghods, Arundhati Banerjee, Jeff Schneider
Active search refers to the problem of efficiently locating targets in an unknown environment by actively making data-collection decisions, and has many applications including dete…
Sparsity-Adaptive Beamspace Channel Estimation for 1-Bit mmWave Massive MIMO Systems
Alexandra Gallyas-Sanhueza, Seyed Hadi Mirfarshbafan, Ramina Ghods +1
We propose sparsity-adaptive beamspace channel estimation algorithms that improve accuracy for 1-bit data converters in all-digital millimeter-wave (mmWave) massive multiple-input…
MSE-Optimal Neural Network Initialization via Layer Fusion
Ramina Ghods, Andrew S. Lan, Tom Goldstein +1
Deep neural networks achieve state-of-the-art performance for a range of classification and inference tasks. However, the use of stochastic gradient descent combined with the nonco…
Reducing the Complexity of Fingerprinting-Based Positioning using Locality-Sensitive Hashing
Larry Tang, Ramina Ghods, Christoph Studer
Localization of wireless transmitters based on channel state information (CSI) fingerprinting finds widespread use in indoor as well as outdoor scenarios. Fingerprinting localizati…
Beamspace Channel Estimation for Massive MIMO mmWave Systems: Algorithm and VLSI Design
Seyed Hadi Mirfarshbafan, Alexandra Gallyas-Sanhueza, Ramina Ghods +1
Millimeter-wave (mmWave) communication in combination with massive multiuser multiple-input multiple-output (MU-MIMO) enables high-bandwidth data transmission to multiple users in…
BEACHES: Beamspace Channel Estimation for Multi-Antenna mmWave Systems and Beyond
Ramina Ghods, Alexandra Gallyas-Sanhueza, Seyed Hadi Mirfarshbafan +1
Massive multi-antenna millimeter wave (mmWave) and terahertz wireless systems promise high-bandwidth communication to multiple user equipments in the same time-frequency resource.…
Optimal Data Detection in Large MIMO
Charles Jeon, Ramina Ghods, Arian Maleki +1
Large multiple-input multiple-output (MIMO) appears in massive multi-user MIMO and randomly-spread code-division multiple access (CDMA)-based wireless systems. In order to cope wit…
Linear Spectral Estimators and an Application to Phase Retrieval
Ramina Ghods, Andrew S. Lan, Tom Goldstein +1
Phase retrieval refers to the problem of recovering real- or complex-valued vectors from magnitude measurements. The best-known algorithms for this problem are iterative in nature…
PhaseLin: Linear Phase Retrieval
Ramina Ghods, Andrew S. Lan, Tom Goldstein +1
Phase retrieval deals with the recovery of complex- or real-valued signals from magnitude measurements. As shown recently, the method PhaseMax enables phase retrieval via convex op…
VLSI Design of a Nonparametric Equalizer for Massive MU-MIMO
Charles Jeon, Gulnar Mirza, Ramina Ghods +2
Linear minimum mean-square error (L-MMSE) equalization is among the most popular methods for data detection in massive multi-user multiple-input multiple-output (MU-MIMO) wireless…
Optimally-Tuned Nonparametric Linear Equalization for Massive MU-MIMO Systems
Ramina Ghods, Charles Jeon, Gulnar Mirza +2
This paper deals with linear equalization in massive multi-user multiple-input multiple-output (MU-MIMO) wireless systems. We first provide simple conditions on the antenna configu…
Optimal Large-MIMO Data Detection with Transmit Impairments
Ramina Ghods, Charles Jeon, Arian Maleki +1
Real-world transceiver designs for multiple-input multiple-output (MIMO) wireless communication systems are affected by a number of hardware impairments that already appear at the…
Optimality of Large MIMO Detection via Approximate Message Passing
Charles Jeon, Ramina Ghods, Arian Maleki +1
Optimal data detection in multiple-input multiple-output (MIMO) communication systems with a large number of antennas at both ends of the wireless link entails prohibitive computat…