I and J

  title={I and J},
  author={William E. Marsden},
On Classical Cloning and No-cloning
Towards Practical Privacy-Preserving Solution for Outsourced Neural Network Inference
A new framework based on synergistic integration of LHE and TEE is proposed, which enables collaboration among mutually-untrusted three parties, while minimizing the involvement of (relatively) resource-constrained TEE and allowing the full utilization of the untrusted but more resource-rich part of server.
Prospective Preference Enhanced Mixed Attentive Model for Session-based Recommendation
This manuscript develops prospective preference enhanced mixed attentive model ( P 2 MAM) to generate session-based recommendations using two important factors: temporal patterns and estimates of users’ prospective preferences.
Dynamical conductivity of disordered quantum chains
We study the transport properties of a one dimensional quantum system with disorder. We numerically compute the frequency dependence of the conductivity of a fermionic chain with nearest neighbor
Global Access to the Internet for All Internet-Draft Network Deployments: Taxonomy, characterization,
  • Computer Science
  • 2022
This document presents a taxonomy of a set of "Alternative Network Deployments" that emerged in the last decade with the aim of bringing Internet connectivity to people or for providing local
A Data-Driven Adaptive Emotion Recognition Model for College Students Using an Improved Multifeature Deep Neural Network Technology
A deep neural network is used to classify the collected emotional EEG data and obtain the emotional state of college students according to the classification results, and the accuracy of emotion recognition exceeds 88%.
Detecting the impact of nuclear reactions on neutron star mergers through gravitational waves
Nuclear reactions may affect gravitational-wave signals from neutron-star mergers, but the impact is uncertain. In order to quantify the effect, we compare two numerical simulations representing
CNNs are Myopic
It is shown experimentally thatCNNs trained only using small seemingly unrecognizable tiles can match or even surpass the performance of CNNs trained on full images, and the proposed a priori theoretical model that seems to explain this behavior is proposed.
TensorCircuit: a Quantum Software Framework for the NISQ Era
TensorCircuit is an open source quantum circuit simulator based on tensor network contraction, designed for speed, flexibility and code efficiency. Written purely in Python, and built on top of