clean base
Roomba Combo j9 review: The ideal robot vacuum and mop
I miss having clean floors. I've been using a variety of Roombas over the years to help out with vacuuming, but ever since my wife and I had our second child in 2022, mopping has become an afterthought. And really, vacuuming can only clean your floor so much. I missed the shimmer of a mopped hardwood floor and the smell of Murphy Oil cleaner lingering in the air. Instead, I've been living with even more toys, crumbs and an assortment of bodily waste (which three cats contribute to) on my flooring and carpets.
The best robot vacuum Black Friday deals for every budget
Black Friday is a great time to pick up big-ticket items while they're deeply discounted, and robot vacuums fit that bill this year. It's not hard to drop hundreds on an autonomous dirt-sucker at any other time of the year, but Black Friday deals have discounted a bunch of our favorite models. Before snagging a deal, think about the type of home you have and how you'll use the machine: do you have carpet or mostly hard flooring? Do you have pets who shed constantly? Do you want a combo vacuum-and-mop machine?
ASSET: Robust Backdoor Data Detection Across a Multiplicity of Deep Learning Paradigms
Pan, Minzhou, Zeng, Yi, Lyu, Lingjuan, Lin, Xue, Jia, Ruoxi
Backdoor data detection is traditionally studied in an end-to-end supervised learning (SL) setting. However, recent years have seen the proliferating adoption of self-supervised learning (SSL) and transfer learning (TL), due to their lesser need for labeled data. Successful backdoor attacks have also been demonstrated in these new settings. However, we lack a thorough understanding of the applicability of existing detection methods across a variety of learning settings. By evaluating 56 attack settings, we show that the performance of most existing detection methods varies significantly across different attacks and poison ratios, and all fail on the state-of-the-art clean-label attack. In addition, they either become inapplicable or suffer large performance losses when applied to SSL and TL. We propose a new detection method called Active Separation via Offset (ASSET), which actively induces different model behaviors between the backdoor and clean samples to promote their separation. We also provide procedures to adaptively select the number of suspicious points to remove. In the end-to-end SL setting, ASSET is superior to existing methods in terms of consistency of defensive performance across different attacks and robustness to changes in poison ratios; in particular, it is the only method that can detect the state-of-the-art clean-label attack. Moreover, ASSET's average detection rates are higher than the best existing methods in SSL and TL, respectively, by 69.3% and 33.2%, thus providing the first practical backdoor defense for these new DL settings. We open-source the project to drive further development and encourage engagement: https://github.com/ruoxi-jia-group/ASSET.
- North America > United States > Virginia > Montgomery County > Blacksburg (0.04)
- North America > United States > Massachusetts > Suffolk County > Boston (0.04)
- Asia > Nepal (0.04)
- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
The best Prime Day robot vacuum deals you can get for 2023
It's always a good idea to look for discounts on big-ticket items on Prime Day, and robot vacuums are no exception. These machines can be some of the most expensive gadgets you buy for your home, with high-end models costing close to (or more than) $1,000 normally. Thankfully, Prime Day is a good time to pick up a robo-vac for much less than that since premium models tend to be hundreds of dollars off, and even those that already have budget-friendly prices are also often discounted. Here are the best robot vacuum Prime Day deals we could find on all of our favorite machines. The iRobot Roomba 694 has dropped to $199 for Prime Day.
How to Sift Out a Clean Data Subset in the Presence of Data Poisoning?
Zeng, Yi, Pan, Minzhou, Jahagirdar, Himanshu, Jin, Ming, Lyu, Lingjuan, Jia, Ruoxi
Given the volume of data needed to train modern machine learning models, external suppliers are increasingly used. However, incorporating external data poses data poisoning risks, wherein attackers manipulate their data to degrade model utility or integrity. Most poisoning defenses presume access to a set of clean data (or base set). While this assumption has been taken for granted, given the fast-growing research on stealthy poisoning attacks, a question arises: can defenders really identify a clean subset within a contaminated dataset to support defenses? This paper starts by examining the impact of poisoned samples on defenses when they are mistakenly mixed into the base set. We analyze five defenses and find that their performance deteriorates dramatically with less than 1% poisoned points in the base set. These findings suggest that sifting out a base set with high precision is key to these defenses' performance. Motivated by these observations, we study how precise existing automated tools and human inspection are at identifying clean data in the presence of data poisoning. Unfortunately, neither effort achieves the precision needed. Worse yet, many of the outcomes are worse than random selection. In addition to uncovering the challenge, we propose a practical countermeasure, Meta-Sift. Our method is based on the insight that existing attacks' poisoned samples shifts from clean data distributions. Hence, training on the clean portion of a dataset and testing on the corrupted portion will result in high prediction loss. Leveraging the insight, we formulate a bilevel optimization to identify clean data and further introduce a suite of techniques to improve efficiency and precision. Our evaluation shows that Meta-Sift can sift a clean base set with 100% precision under a wide range of poisoning attacks. The selected base set is large enough to give rise to successful defenses.
- North America > United States > Virginia > Montgomery County > Blacksburg (0.04)
- Asia > Nepal (0.04)
- Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Performance Analysis > Accuracy (1.00)
- Information Technology > Data Science (0.93)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.93)
iRobot's Roomba j7 Combo vacuum is $300 off right now
Avoiding manual floor maintenance is a lovely thing, but a good robot vacuum will cost you. Our current favorite pick for a mop and vac combo, iRobot's Roomba j7 usually sells for $1,099 but Wellbots will knock $300 off the list price when you use the code 300ENGADGET at checkout. That beats a $200 discount we saw earlier this year and represents an all-time low for a gadget that "earned its place" in on of our senior editors' smart home. Wellbots has a few other vacs on sale too, also with discount codes, listed below. Our top pick for a mop and vacuum combo is $300 off right now when you use the code 300ENGADGET at checkout.
iRobot's Roomba Combo j7 vacuum and mop is $200 off right now
If you need a little help keeping your home clean in the new year, a robot vacuum can help. It may not be an essential piece of tech, especially if you already have a decent vacuum, but it can make consistent cleaning much easier by letting you automate a portion of the process. Wellbots has a number of Roomba robot vacuums on sale right now, including the new Combo j7, which is iRobot's first vac-and-mop device. You can pick that up for $200 less than usual with the code ENG200 at checkout, while the standard Roomba j7 and the s9 are $200 off as well with the same code. Use the code ENG200 at checkout to get $200 of this machine that vacuums and has a water reservoir for when you want it to mop hard floors.
iRobot's premium Roomba s9 robot vacuum is $220 off right now
The Roomba s9 has been around for a couple of years and it's probably overkill for most people. At $999, it's certainly not cheap, but it did earn a spot in our list of best robot vacuums. Right now, you can pick up the high-end machine for $220 less than usual by shopping through Wellbots and using the code ENG220 at checkout. A final price of $779 is the best we've seen on this smart home gadget, and while it's still an expensive device, it's a much easier to recommend when its on sale like this. You probably don't need all of the bells and whistles that the s9 provides, but they are some of the things that make it one of the best robot vacuums available today.
- Information Technology > Smart Houses & Appliances (0.58)
- Retail (0.54)
The best Black Friday tech deals for 2022
Black Friday is finally here and if you haven't started your holiday shopping, now's the best time to do so. While we've seen some of our favorite gadgets go on sale since the start of November, today's the day you're almost guaranteed to find the best prices of the year across laptops, TVs, speakers, tablets, wearables and much more. But, as usual, the sheer volume of deals across the web today makes it even harder to pick out the gems among them. There are absolutely tech "deals" out there today that are not worth your time. To make ease the burden of deal-hunting, we collected the best Black Friday tech deals we could find right here.
The best early Black Friday tech deals for 2022
Black Friday may still be a few hours away, but we're already seeing a bunch of great deals on our favorite tech. This comes after a slow trickle of deals popping up across the web ever since the start of November. While we don't have the supply chain issues we did last year, it's still a good idea to start your holiday shopping as early as possible -- even if it's just a few hours before the biggest sale day of the year. The sooner you check off items from your list, the sooner they'll arrive and you'll be ready to go for the holidays. To make things easier for you, we've collected the best early Black Friday tech deals here so you don't have to go searching for them.