February 26, 2024

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Optimised Neural Network for a Better Accuracy

The neural network has been used to assist humans with everything from determining whether a loan applicant will be approved to deciding whether or not a patient has a specific illness. But many aspects of neural networks are still poorly understood by researchers.

Machine learning models inspired by the human brain are called neural networks. Data is processed by a network of synapses with many levels of connections. Scientists teach a network to operate by feeding it millions of data samples.

For instance, an encoded picture could be presented to a network that has been taught to distinguish between, say, dogs and cats. Layer by layer, the network executes a complex multiplication until only one number remains. Then, the network decides whether the image is of a dog or a cat based on whether or not that figure is optimistic.

It is still being determined whether any specific model is the best choice for a particular job. The team at MIT has chosen to investigate and find out more. They analysed neural networks and demonstrated that they could be optimised to reduce the likelihood of misclassifying debtors or patients when given a large amount of labelled training data. These networks must be constructed with a particular architecture to function efficiently.

The study’s authors uncovered that developers sometimes use the building elements that make for an optimal neural network. Researchers claim that the optimal building blocks they deduce from the new analysis are novel and have never been studied.

These optimal building elements, called activation functions, are described in a paper reported this week in the Proceedings of the National Academy of Sciences. The components demonstrate how they can be incorporated into developing neural networks that outperform the competition on any dataset.

The findings remain consistent even when the size of the neural networks is enormous. According to the study’s senior author and EECS professor Caroline Uhler, developers can create neural networks that classify data more accurately across many domains if they choose the proper activation function.

The activation functions aid the network in discovering intricate structures in the data. They transform the data after each tier before sending it to the next. Scientists must settle on a single activation function when developing a neural network. They also select the network’s breadth (the number of synapses per layer) and depth of how many layers are in the network.

To quote the paper: “It turns out that, if you take the standard activation functions that people use in practise and keep raising the depth of the network, it gives you terrible performance,” Adityanarayanan Radhakrishnan, a graduate student in electrical and computer engineering, is the paper’s lead author explained. “We show that if you design with different activation functions, your network will improve as you get more data.”

The team investigated a neural network that is infinitely deep and wide, meaning that it is constructed by continuously adding more layers and nodes and is then taught to carry out classification tasks. The network learns to classify data sources into distinct groups through the classification process.

They tested this theory on several classification benchmarking tasks and found that, in many instances, it led to better performance. Furthermore, their methods could be used by neural network designers to choose an activation function with higher classification accuracy.

Researchers hope to apply their findings to future analyses of less-than-ideal data sets and networks constrained in scope and depth. They are also interested in expanding this research to unlabelled data sets.

PARTNER

Qlik’s vision is a data-literate world, where everyone can use data and analytics to improve decision-making and solve their most challenging problems. A private company, Qlik offers real-time data integration and analytics solutions, powered by Qlik Cloud, to close the gaps between data, insights and action. By transforming data into Active Intelligence, businesses can drive better decisions, improve revenue and profitability, and optimize customer relationships. Qlik serves more than 38,000 active customers in over 100 countries.

PARTNER

CTC Global Singapore, a premier end-to-end IT solutions provider, is a fully owned subsidiary of ITOCHU Techno-Solutions Corporation (CTC) and ITOCHU Corporation.

Since 1972, CTC has established itself as one of the country’s top IT solutions providers. With 50 years of experience, headed by an experienced management team and staffed by over 200 qualified IT professionals, we support organizations with integrated IT solutions expertise in Autonomous IT, Cyber Security, Digital Transformation, Enterprise Cloud Infrastructure, Workplace Modernization and Professional Services.

Well-known for our strengths in system integration and consultation, CTC Global proves to be the preferred IT outsourcing destination for organizations all over Singapore today.

PARTNER

Planview has one mission: to build the future of connected work. Our solutions enable organizations to connect the business from ideas to impact, empowering companies to accelerate the achievement of what matters most. Planview’s full spectrum of Portfolio Management and Work Management solutions creates an organizational focus on the strategic outcomes that matter and empowers teams to deliver their best work, no matter how they work. The comprehensive Planview platform and enterprise success model enables customers to deliver innovative, competitive products, services, and customer experiences. Headquartered in Austin, Texas, with locations around the world, Planview has more than 1,300 employees supporting 4,500 customers and 2.6 million users worldwide. For more information, visit www.planview.com.

SUPPORTING ORGANISATION

SIRIM is a premier industrial research and technology organisation in Malaysia, wholly-owned by the Minister​ of Finance Incorporated. With over forty years of experience and expertise, SIRIM is mandated as the machinery for research and technology development, and the national champion of quality. SIRIM has always played a major role in the development of the country’s private sector. By tapping into our expertise and knowledge base, we focus on developing new technologies and improvements in the manufacturing, technology and services sectors. We nurture Small Medium Enterprises (SME) growth with solutions for technology penetration and upgrading, making it an ideal technology partner for SMEs.

PARTNER

HashiCorp provides infrastructure automation software for multi-cloud environments, enabling enterprises to unlock a common cloud operating model to provision, secure, connect, and run any application on any infrastructure. HashiCorp tools allow organizations to deliver applications faster by helping enterprises transition from manual processes and ITIL practices to self-service automation and DevOps practices. 

PARTNER

IBM is a leading global hybrid cloud and AI, and business services provider. We help clients in more than 175 countries capitalize on insights from their data, streamline business processes, reduce costs and gain the competitive edge in their industries. Nearly 3,000 government and corporate entities in critical infrastructure areas such as financial services, telecommunications and healthcare rely on IBM’s hybrid cloud platform and Red Hat OpenShift to affect their digital transformations quickly, efficiently and securely. IBM’s breakthrough innovations in AI, quantum computing, industry-specific cloud solutions and business services deliver open and flexible options to our clients. All of this is backed by IBM’s legendary commitment to trust, transparency, responsibility, inclusivity and service.

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