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Comparison of partial least squares-discriminant analysis, support vector machines and deep neural networks for spectrometric classification of seed vigour in a broad range of tree species
least squares-discriminant analysis spectrometric classification seed tree species
2023/6/5
Seed vigour significantly influences the seed production and plant regeneration performance. The capability of NIR spectroscopy to identify seed vigour across multiple tree species rapidly and cost-ef...
Output Compression, MPC, and iO for Turing Machines
Randomized encodings compact MPC indistinguishability obfuscation
2018/11/13
In this work, we study the fascinating notion of output-compressing randomized encodings for Turing Machines, in a shared randomness model. In this model, the encoder and decoder have access to a shar...
FE and iO for Turing Machines from Minimal Assumptions
indistinguishability obfuscation functional encryption Turing machines
2018/11/9
We construct Indistinguishability Obfuscation (iO) and Functional Encryption (FE) schemes in the Turing machine model from the minimal assumption of compact FE for circuits (CktFE). Our constructions ...
We give a simple construction of indistinguishability obfuscation for Turing machines where the time to obfuscate grows only with the description size of the machine and otherwise, independent of the ...
Image Classification using non-linear Support Vector Machines on Encrypted Data
cryptographic protocols SHE
2017/9/13
In image processing, algorithms for object classification are typically based around machine learning. From the algorithm developer's perspective, these can involve a considerable amount of effort and...
Attribute-Based Signatures for Turing Machines
attribute-based signatures Turing machines indistinguishability obfuscation
2017/8/29
Attribute-based signatures (ABS) support restricted signing keys which allow signers to sign messages with respect to specific signing credentials or attributes that are accepted by the signing polici...
BALANCED VS IMBALANCED TRAINING DATA:CLASSIFYING RAPIDEYE DATA WITH SUPPORT VECTOR MACHINES
Land cover classification Imbalanced training data Support Vector Machines RapidEye Agriculture
2016/11/23
The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imager...
Efficient and Private Scoring of Decision Trees, Support Vector Machines and Logistic Regression Models based on Pre-Computation
privacy-preserving private data
2016/7/29
Many data-driven personalized services require that private data of users is scored against a trained machine learning model. In this paper we propose a novel protocol for privacy-preserving classific...
LAND COVER CLASSIFICATION FROM FULL-WAVEFORM LIDAR DATA BASED ON SUPPORT VECTOR MACHINES
LiDAR Support Vector Machines (SVM) Full-Waveform Land Cover Classification Waveform decomposition Feature extraction
2016/7/27
In this study, a land cover classification method based on multi-class Support Vector Machines (SVM) is presented to predict the types of land cover in Miyun area. The obtained backscattered full-wave...
We pose the question whether the asymptotic equivalence between quantum cloning and quantum state estimation, valid at the single-clone level, still holds when all clones are examined globally. We con...
Sentiment-Aspect Extraction based on Restricted Boltzmann Machines
Sentiment-Aspect Extraction Restricted Boltzmann Machines
2016/1/22
Aspect extraction and sentiment analysis of reviews are both important tasks in opinion mining. We propose a novel senti-mentandaspectextractionmodelbasedon Restricted Boltzmann Machines to jointly ad...
Bounded Rationality of Restricted Turing Machines
bounded rationality repeated games restricted Turing machine
2016/1/22
Bounded rationality aims to understand the effects of how limited rationality affects decision-making. The traditional models in game theory and multiagent system research, such as finite automata or ...
Indistinguishability Obfuscation for Turing Machines with Unbounded Memory
Turing Machines Unbounded Memory
2016/1/6
We show how to build indistinguishability obfuscation (iO) for Turing Machines where the overhead
is polynomial in the security parameter λ, machine description |M| and input size |x| (with only a
n...
ANALYSIS OF THE TRANSFERABILITY OF SUPPORT VECTOR MACHINES FOR VEGETATION CLASSIFICATION
Remote Sensing Mapping Classification Accuracy High resolution Ikonos
2015/12/31
This paper reports on research analysing the potential of Support Vector Machines (SVMs) for mapping vegetation from high spatial resolution Ikonos imagery. The work investigated the utility of SVMs f...
Message Transmission with Reverse Firewalls---Secure Communication on Corrupted Machines
reverse firewalls exfiltration secure message transmission
2015/12/30
A secure reverse firewall, as recently defined by Mironov and Stephens-Davidowitz, is a
third party that “sits between a user and the outside world” and modifies the user’s sent and received
message...