Learning binary relations using weighted majority voting

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252 GOLDMAN AND WARMUTH the learning problem among themselves. Assume M~j is the next value to predict. To make its prediction, the node for row r combines the votes of the n - 1 inputs from column j of matrix M. Each node r ~ ¢ r votes with the weight w(er
LEARNING BINARY RELATIONS 253 Learn-Relation(O _< 7 < 1) For all r,r' such that (r ¢ r') initialize w(e~
Page 1 and 2: Machine Leaming, 20, 245-271 (1995)
Page 3 and 4: LEARNING BINARY RELATIONS 247 When
Page 5 and 6: LEARNING BINARY RELATIONS 249 ~,~,.
Page 7: LEARNING BINARY RELATIONS 251 l J i
Page 11 and 12: LEARNING BINARY RELATIONS 255 We no
Page 13 and 14: LEARNING BINARY RELATIONS 257 Solvi
Page 15 and 16: LEARNING BINARY RELATIONS 259 In th
Page 17 and 18: LEARNING BINARY RELATIONS 261 depen
Page 19 and 20: LEARNING BINARY RELATIONS 263 m V S
Page 21 and 22: LEARNING BINARY RELATIONS 265 Final
Page 23 and 24: LEARNING BINARY RELATIONS 267 32500
Page 25 and 26: LEARNING BINARY RELATIONS 269 mance
Page 27: LEARNING BINARY RELATIONS 271 Kivin

Learning binary relations using weighted majority voting

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