5.2k citations
- Courant Institute of Mathematical SciencesUS7 papers
- Columbia UniversityUS5 papers
- New York UniversityUS5 papers
- Cornell UniversityUS4 papers
- Microsoft (United States)US4 papers
- University of California, BerkeleyUS4 papers
- University of Illinois Urbana-ChampaignUS4 papers
- University of WashingtonUS4 papers
- Carnegie Mellon UniversityUS3 papers
- Massachusetts Institute of TechnologyUS3 papers
- Stanford UniversityUS3 papers
- Bharathidasan UniversityIN2 papers
4 papers · 2 filters
Optimal amortized regret in every interval
Rina Panigrahy, Preyas Popat
Consider the classical problem of predicting the next bit in a sequence of bits. A standard performance measure is {\em regret} (loss in payoff) with respect to a set of experts. F…
Fractal structures in Adversarial Prediction
Rina Panigrahy, Preyas Popat
Fractals are self-similar recursive structures that have been used in modeling several real world processes. In this work we study how "fractal-like" processes arise in a predictio…
Large-Scale Learning with Less RAM via Randomization
Daniel Golovin, D. Sculley, H. Brendan McMahan +1
We reduce the memory footprint of popular large-scale online learning methods by projecting our weight vector onto a coarse discrete set using randomized rounding. Compared to stan…
A Semantic Matching Energy Function for Learning with Multi-relational Data
Xavier Glorot, Antoine Bordes, Jason Weston +1
Large-scale relational learning becomes crucial for handling the huge amounts of structured data generated daily in many application domains ranging from computational biology or i…