Sign Cauchy Projections and Chi-Square Kernel
–Neural Information Processing Systems
In this paper, we propose to use only the signs of the projected data and we analyze the probability of collision (i.e., when the two signs differ). Interestingly, when α = 1 (i.e., Cauchy random projections), we show that the probability of collision can be accurately approximated as functions of the chi-square (χ
Neural Information Processing Systems
Mar-13-2024, 15:37:23 GMT
- Country:
- Asia
- Afghanistan > Parwan Province
- Charikar (0.04)
- Middle East > Lebanon (0.04)
- Afghanistan > Parwan Province
- Europe
- Netherlands > North Holland
- Amsterdam (0.04)
- United Kingdom > Wales
- Ceredigion > Aberystwyth (0.04)
- Netherlands > North Holland
- North America
- Barbados (0.04)
- Canada
- British Columbia > Metro Vancouver Regional District
- Vancouver (0.04)
- Quebec > Montreal (0.04)
- British Columbia > Metro Vancouver Regional District
- United States
- California
- San Francisco County > San Francisco (0.14)
- Santa Clara County > San Jose (0.04)
- Florida > Miami-Dade County
- Miami (0.04)
- New York > Tompkins County
- Ithaca (0.04)
- Oregon (0.04)
- Pennsylvania > Allegheny County
- Pittsburgh (0.04)
- Texas > Dallas County
- Dallas (0.04)
- California
- Asia
- Genre:
- Research Report > New Finding (0.68)
- Technology: