✔ 100% Money-Back Guarantee on Eligible Items
✔ Prices Displayed in Your Local Currency
✔ Final Price = No Surprise Import Fees
✔ Complimentary Insured Worldwide Shipping on Qualifying Orders
✔ Select Collector & Specialty Pieces May Require Secured Delivery Handling
by Aleksandr Aravkin (Editor), Anna Choromanska (Editor), Li Deng (Editor)
Advances in training models with log-linear structures, with topics including variable selection, the geometry of neural nets, and applications.
Log-linear models play a key role in modern big data and machine learning applications. From simple binary classification models through partition functions, conditional random fields, and neural nets, log-linear structure is closely related to performance in certain applications and influences fitting techniques used to train models. This volume covers recent advances in training models with log-linear structures, covering the underlying geometry, optimization techniques, and multiple applications. The first chapter shows readers the inner workings of machine learning, providing insights into the geometry of log-linear and neural net models. The other chapters range from introductory material to optimization techniques to involved use cases. The book, which grew out of a NIPS workshop, is suitable for graduate students doing research in machine learning, in particular deep learning, variable selection, and applications to speech recognition. The contributors come from academia and industry, allowing readers to view the field from both perspectives. ContributorsAleksandr Aravkin, Avishy Carmi, Guillermo A. Cecchi, Anna Choromanska, Li Deng, Xinwei Deng, Jean Honorio, Tony Jebara, Huijing Jiang, Dimitri Kanevsky, Brian Kingsbury, Fabrice Lambert, Aur?lie C. Lozano, Daniel Moskovich, Yuriy S. Polyakov, Bhuvana Ramabhadran, Irina Rish, Dimitris Samaras, Tara N. Sainath, Hagen Soltau, Serge F. Timashev, Ewout van den Berg
Author Biography
Aleksandr Aravkin is Assistant Professor of Applied Mathematics at the University of Washington.
Anna Choromanska is Assistant Professor at New York University's Tandon School of Engineering. Li Deng is Chief Artificial Intelligence Officer of Citadel. Georg Heigold is Research Scientist at Google. Tony Jebara is Associate Professor of Computer Science at Columbia University. Dimitri Kanevsky is Research Scientist at Google. Stephen J. Wright is Professor of Computer Science at the University of Wisconsin-Madison.- In stock, ready to ship
- ✔ Authenticity Guaranteed — Verified Designer Goods
- ✔ Sourced from Authorized European/U.S. Luxury Distributors
- ✔ Secure Checkout — SSL Encrypted Payments
- ✔ Fast Global Delivery — 3–11 Business Days
- ✔ Easy Returns on Eligible Items
- ✔ 100% Money-Back Guarantee — Full Refund if Not Satisfied
AUTHENTICITY GUARANTEED
Reserved for you — complete your purchase to secure this piece.
OFFICIALLY AUTHORIZED RESELLER
Discover Officially Authorized Authentic Items at STORE7994.com - Certificates Available on Request!
Independently verified for store quality and customer safety.
Trust score: 91/100
All designer items offered by STORE 7994 are sourced from trusted luxury distributors and verified through independent authentication services.
Learn how STORE 7994 authenticates luxury items
Guaranteed Authentic — Includes Brand Documentation & Third-Party Verification Options.
Shipping information
- Free Shipping* on all orders over $300 USD to most countries* Estimated delivery: 2-5 business days Mon-Sat to U.S., CA, EU etc.
- Tracking available: DHL Express
- Store 7994 Shipping policy
- Global delivery in 3–9 business days (location dependent).
- Free Worldwide Shipping $300+. International duties & VAT are calculated by destination country and may be collected upon delivery. UK orders are subject to 20% import VAT upon delivery.

Our innovation isn’t just in the brands we carry — it’s in the way we connect them. From our automation engine that keeps collections globally updated to our commitment to authenticity-first presentation, STORE 7994 exists where timeless design meets modern precision.
Every product we offer is:
Elevated · Intentional · Exclusive · Authentic
STORE 7994 is an authorized reseller of luxury fashion houses. Certificates and proof of authenticity are available to brand owners and partners upon request.
Returns & Refunds
We want you to shop with confidence at STORE 7994. If your purchase does not meet expectations, eligible items may be returned under the conditions below.
Return Eligibility
Items must be unused, unworn, and in original condition with all tags, packaging, and accessories included. Items showing any signs of wear or damage will not be accepted.
Return Window
Return requests must be made within 14 days of delivery.
Return Shipping
Customers are responsible for return shipping costs unless the item is defective, damaged, or incorrect.
Luxury Items
Items valued over $1,000 may be subject to a 7% restocking fee upon approved return.
Non-Returnable Items
For hygiene and product integrity reasons, the following items are final sale once opened or used:
• Underwear
• Fragrances
• Any worn or used items
Made-to-Order Items
Custom-designed products, including STORE 7994 hoodies, are made exclusively for each customer and are final sale. These items are not eligible for return or exchange unless defective or incorrect.
If you receive a defective or incorrect item, please contact us and we will make it right.
International Shipping & Duties
Many of our products ship directly from trusted international partners. Any applicable customs duties or import taxes are calculated at checkout and are non-refundable, even if the item is returned.
Returns & Associated Fees
All approved returns are subject to a $24 return processing fee. For international orders, duties, taxes, and return fees will be deducted from the original payment.
Shipping Policy
Complimentary shipping is offered on orders over $300. Orders below this threshold are subject to standard shipping rates at checkout.
>