edu.stanford.nlp.math

• ```public class ADMath
extends Object```
The class `ADMath` was created to extend the current calculations of gradient to automatically include a calculation of the hessian vector product with another vector `v`. It contains all the functions for the DoubleAlgorithmicDifferentiation class. This is used with Stochastic Meta Descent Optimization, but could be extended for use in any application that requires an additional order of differentiation without explicitly creating the code.
Version:
2006/12/06
Author:
Alex Kleeman
• ### Method Summary

All Methods
Modifier and Type Method and Description
`static DoubleAD` ```divide(DoubleAD a, DoubleAD b)```
`static DoubleAD` ```divideConst(DoubleAD a, double b)```
`static DoubleAD` `exp(DoubleAD a)`
`static DoubleAD` `log(DoubleAD a)`
`static DoubleAD` `logSum(DoubleAD[] logInputs)`
`static DoubleAD` ```logSum(DoubleAD[] logInputs, int fromIndex, int toIndex)```
`static DoubleAD` ```minus(DoubleAD a, DoubleAD b)```
`static DoubleAD` ```minusConst(DoubleAD a, double b)```
`static DoubleAD` ```mult(DoubleAD a, DoubleAD b)```
`static DoubleAD` ```multConst(DoubleAD a, double b)```
`static DoubleAD` ```plus(DoubleAD a, DoubleAD b)```
`static DoubleAD` ```plusConst(DoubleAD a, double b)```
• ### Methods inherited from class java.lang.Object

`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`
• ### Method Detail

• #### mult

```public static DoubleAD mult(DoubleAD a,
• #### multConst

```public static DoubleAD multConst(DoubleAD a,
double b)```
• #### divide

```public static DoubleAD divide(DoubleAD a,
• #### divideConst

```public static DoubleAD divideConst(DoubleAD a,
double b)```
• #### exp

`public static DoubleAD exp(DoubleAD a)`
• #### log

`public static DoubleAD log(DoubleAD a)`
• #### plus

```public static DoubleAD plus(DoubleAD a,
• #### plusConst

```public static DoubleAD plusConst(DoubleAD a,
double b)```
• #### minus

```public static DoubleAD minus(DoubleAD a,
• #### minusConst

```public static DoubleAD minusConst(DoubleAD a,
double b)```
• #### logSum

`public static DoubleAD logSum(DoubleAD[] logInputs)`
• #### logSum

```public static DoubleAD logSum(DoubleAD[] logInputs,
int fromIndex,
int toIndex)```

Stanford NLP Group