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Filtering by: Creator Shepherd, Stephen H. Academic Affiliation Electrical Engineering and Computer Science Contributor Fu, Xiao

Graph Imitation Learning for Optimal Joint Beamforming and Antenna Selection

Creator:

Shrestha, Sagar

Abstract:

Transmit beamforming is an important technique employed to improve efficiency and signal quality in wireless communication systems by steering signals towards their in- tended users. It often arises jointly with the antenna selection problem due to various reasons, such as limited number of radio frequency (RF) chains and energy/resource effi-...

Resource Type:

Masters Thesis

Full Text:

received by user m can be expressed as follows: ym(t) = h H mwmsm(t)︸︷︷︸ signal + ∑ ℓ̸=m hHmwℓsℓ(t
Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

Creator:

Khorram, Saeed

Abstract:

In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...

Resource Type:

Masters Thesis

Full Text:

place (front). Here, Heatmaps (H) 1-5&7 are toggled on and Heatmap (H) 6 is toggled off
Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

Creator:

Seo, Eugene

Abstract:

Ecological domains seeking to understand the environment and the behavior of species have received little attention in machine learning (ML), despite the fact that environmental changes have a significant impact on humans as well as ecosystems. Some ecological problems can be formulated similarly to other common ML applications, but there...

Resource Type:

Dissertation

Full Text:

, and Dr. Stephen Ramsey, for providing constructive feedback and comments through the process. I am

ScholarsArchive@OSU

Graph Imitation Learning for Optimal Joint Beamforming and Antenna Selection

Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

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