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Nozomu Togawa

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Professor

Waseda University

Japan

Research Interests

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Professors in Japan Professors in Condensed Matter Physics Condensed Matter Physics professors in Japan

About

Professor Nozomu Togawa is a faculty member at Waseda University in Japan. His research areas focus on combinatorial optimization, quantum computing, and machine learning, as demonstrated in his recent articles that explore topics such as hardware Trojan detection, personalized course selection, and multi-day intermodal trip planning. Professor Togawa is dedicated to advancing knowledge in these fields through innovative approaches and methodologies.

Recent Grants

Grant: Close

Hardware-Trojan Detection for Integrated Circuit Design Data based on Machine Learning

Open Date: 2019-04-01

Close Date: 2022-03-31

Grant: Close

再構成アクセラレータにおけるデータ形式最適化と精度保証

Open Date: 2018-04-01

Close Date: 2021-03-31

Grant: Close

Bit-write minimizing codes for non-volatile memories and their application to normally-off computing

Open Date: 2017-06-30

Close Date: 2019-03-31

Grant: Close

Efficient Subtract-Multiply Operation Circuit Design Using Selector Logics

Open Date: 2013-04-01

Close Date: 2015-03-31

Grant: Close

Abstract LSI model and Its Associated Low-energy Integrated LSI Design Methodology

Open Date: 2013-04-01

Close Date: 2016-03-31

Articles (19)

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2021

Collaborators (2)

Shuta Kikuchi

Project Lecturer

Keio University

JAPAN

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Shu Tanaka

Professor

Keio University

JAPAN

View details

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Nozomu Togawa

Research Interests

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About

Recent Grants

Articles (19)

Linearizing Binary Optimization Problems Using Variable Posets for Ising Machines

An Ising Machine Approach to the Personalized Course Selection Problem

Compressed Space Quantum Approximate Optimization Algorithm for Constrained Combinatorial Optimization

Hybrid subQUBO Annealing With a Correction Process for Multi-Day Intermodal Trip Planning

A GPU-Based Ising Machine With a Multi-Spin-Flip Capability for Constrained Combinatorial Optimization

An Ising-Machine-Based Solver of Vehicle Routing Problem With Balanced Pick-Up

Ising Machine Approach to the Lecturer–Student Assignment Problem

Postprocessing Variationally Scheduled Quantum Algorithm for Constrained Combinatorial Optimization Problems

QUBO Formulation Using Sequence Pair With Search Space Restriction for Rectangle Packing Problem

R-HTDetector: Robust Hardware-Trojan Detection Based on Adversarial Training

Dynamical Process of a Bit-Width Reduced Ising Model With Simulated Annealing

Node-wise Hardware Trojan Detection Based on Graph Learning

Spin-Variable Reduction Method for Handling Linear Equality Constraints in Ising Machines

Trip Planning Based on subQUBO Annealing

Hybrid Annealing Method Based on subQUBO Model Extraction With Multiple Solution Instances

Multi-Objective Trip Planning Based on Ant Colony Optimization Utilizing Trip Records

A Three-Stage Annealing Method Solving Slot-Placement Problems Using an Ising Machine

A route recommendation method considering individual user’s preferences by monte-carlo tree search and its evaluations

Generating adversarial examples for hardware-trojan detection at gate-level netlists

Collaborators (2)

Shuta Kikuchi

Shu Tanaka

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