Joel Gibson – författare

Kill Bills! is the bible for saving thousands of dollars on your major household bills. From power bills to telco, mortgage, insurance, credit cards, petrol and groceries, it describes the 9 Insider Tricks You Need to Win the War on Household Bills.  You'll start saving straight away thanks to simple strategies with names like ‘The De Niro’, ‘The Mystery-Shopper’, ‘The Elizabeth Taylor’ and ‘The Red Dog’. Backed by the team of money-saving experts at One Big Switch, Joel Gibson has gathered 7 years of shortcuts, hacks and loopholes – all so you don’t have to.   In a hurry? There’s a step-by-step guide to saving over $1000 in an afternoon.Got a big power bill or insurance renewal? Kill Bills! will help you take the power – and the dollars – back with in-depth chapters on 9 of the major household bills and how those industries work.Want to become a fully-fledged money-saving black belt? Read this book from cover to cover and it will arm you with everything you need to kick some serious household bill backside! This audio edition is narrated by Kill Bills! author Joel Gibson. It includes an appendix of website links mentioned in the book in PDF for listeners to download and use.

Kill Bills! is the bible for saving thousands of dollars on your major household bills. From power bills to telco, mortgage, insurance, credit cards, petrol and groceries, it describes the 9 Insider Tricks You Need to Win the War on Household Bills.  You'll start saving straight away thanks to simple strategies with names like ‘The De Niro’, ‘The Mystery-Shopper’, ‘The Elizabeth Taylor’ and ‘The Red Dog’. Backed by the team of money-saving experts at One Big Switch, Joel Gibson has gathered 7 years of shortcuts, hacks and loopholes – all so you don’t have to.   In a hurry? There’s a step-by-step guide to saving over $1000 in an afternoon.Got a big power bill or insurance renewal?Kill Bills! will help you take the power – and the dollars – back with in-depth chapters on 9 of the major household bills and how those industries work.Want to become a fully-fledged money-saving black belt? Read this book from cover to cover and it will arm you with everything you need to kick some serious household bill backside!

Discover how to save $1000+ with Joel Gibson’s easy, quick money-saving tips. Maximise your budget in the cost-of-living crisis and reduce your bills as inflation and interest rates continue to rise.   Australian households are facing the toughest cost of living crisis in years, but most of us are still spending more than we need to on household costs. Easy Money is here to help you get some of that money back, with minimal effort and speedy results.   Joel Gibson, Australia’s #1 money-saving expert, will teach you the seven simple steps to saving $1000+ in just one afternoon.   Some of Joel’s tips include: The easiest ways to slash energy, telco, insurance and housing costs Simple new money-saving hacks for getting a better deal on groceries and petrol How to save hundreds on streaming and pay TV How to get ‘free money’ from government rebates Easy Money is a practical, simple guide that will help you save money without any stress.

This brief focuses on two main problems in the domain of optical flow and trajectory estimation: (i) The problem of finding convex optimization methods to apply sparsity to optical flow; and (ii) The problem of how to extend sparsity to improve trajectories in a computationally tractable way.Beginning with a review of optical flow fundamentals, it discusses the commonly used flow estimation strategies and the advantages or shortcomings of each. The brief also introduces the concepts associated with sparsity including dictionaries and low rank matrices. Next, it provides context for optical flow and trajectory methods including algorithms, data sets, and performance measurement. The second half of the brief covers sparse regularization of total variation optical flow and robust low rank trajectories. The authors describe a new approach that uses partially-overlapping patches to accelerate the calculation and is implemented in a coarse-to-fine strategy. Experimental results show that combining total variation and a sparse constraint from a learned dictionary is more effective than employing total variation alone.The brief is targeted at researchers and practitioners in the fields of engineering and computer science. It caters particularly to new researchers looking for cutting edge topics in optical flow as well as veterans of optical flow wishing to learn of the latest advances in multi-frame methods.