Table of Contents

Neural Networks for Fashion Image Classification and Visual Search

Li Fengzi, National University of Singapore (NUS)
Shashi Kant, National University of Singapore (NUS)
Shunichi Araki, National University of Singapore (NUS)
Sumer Bangera, National University of Singapore (NUS)
Swapna Samir Shukla, National University of Singapore (NUS)

Reward Value Revealed by Auction in Rhesus Monkeys

Alaa Al-Mohammad, University of Cambridge
Wolfram Schultz, University of Cambridge - Department of Physiology, Development and Neuroscience


"Neural Networks for Fashion Image Classification and Visual Search" Free Download

LI FENGZI, National University of Singapore (NUS)
SHASHI KANT, National University of Singapore (NUS)
SHUNICHI ARAKI, National University of Singapore (NUS)
SUMER BANGERA, National University of Singapore (NUS)
SWAPNA SAMIR SHUKLA, National University of Singapore (NUS)

We discuss two potentially challenging problems faced by the ecommerce industry. One relates to the problem faced by sellers while uploading pictures of products on the platform for sale and the consequent manual tagging involved. It gives rise to misclassifications leading to its absence from search results. The other problem concerns with the potential bottleneck in placing orders when a customer may not know the right keywords but has a visual impression of an image. An image based search algorithm can unleash the true potential of ecommerce by enabling customers to click a picture of an object and search for related projects without the need for typing. In this paper, we explore machine learning algorithms which can help us solve both these problems.

"Reward Value Revealed by Auction in Rhesus Monkeys" Free Download

ALAA AL-MOHAMMAD, University of Cambridge
WOLFRAM SCHULTZ, University of Cambridge - Department of Physiology, Development and Neuroscience

Economic choice is thought to involve the elicitation of the private and subjective values of various choice options. Thus far, the estimation of subjective values in animals has relied upon repeated choices and was expressed as an average from dozens of stochastic decisions. However, decisions are made moment-to-moment, and their consequences are usually felt immediately. Here we describe a Becker-DeGroot-Marschak (BDM) auction-like mechanism that encourages animals to truthfully reveal their subjective value in individual choices. The monkeys reliably placed well-ranked BDM bids for up to five juice volumes while paying from a water budget. The bids closely approximated the average subjective values estimated with conventional binary choices, thus demonstrating procedural invariance and aligning with the wealth of knowledge acquired with these less direct estimates. The feasibility of BDM bidding in monkeys encourages single-trial neuronal studies and bridges the gap to the widely used BDM method in human neuroeconomics.


About this eJournal

This area includes content focused on research where economic outcomes are the product of many individual decisions, constrained by scarcity, and equilibrium forces that simultaneously shape a person's social networks and the institutionally defined rules of the game. Decisions are made by computations in the brain which produce action-choices that directly affect the homeostatic wellbeing of the individual and choices that indirectly change wellbeing by changing an individual's future constraints, the scope of their social networks, and their message sending rights within the institutions they participate. Neuroeconomics broadly speaking is interested in the study of these computations and the resulting choices they produce. This includes experiments that attempt to understand the mechanisms of neuronal computations that produce action-choices, theories which predict how neuronal computations in socio-economic environments produce decisions, outcomes and wellbeing, and policy which use our understanding of neuoroeconomic behavior to either build or defend better solutions to societal problems.

Editors: Michael C. Jensen, Harvard University, and Kevin A. McCabe, George Mason University


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Advisory Board

Neuroeconomics eJournal

Harris & Harris Group Professor, Massachusetts Institute of Technology (MIT) - Sloan School of Management, National Bureau of Economic Research (NBER), Principal Investigator, Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Professor, Baylor University - Department of Neuroscience

Professor of Economics and Law, Chapman University - Economic Science Institute, Chapman University School of Law