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Running
| { | |
| "algorithms": [ | |
| { | |
| "id": "gradient_descent", | |
| "label": "Gradient descent", | |
| "params": [ | |
| { "name": "learning_rate", "label": "Learning rate η", "symbol": "η", "kind": "number", "min": 0, "minExclusive": true, "default": 0.1, "description": "How far each step moves along the negative gradient." }, | |
| { "name": "momentum", "label": "Momentum μ", "symbol": "μ", "kind": "number", "min": 0, "max": 1, "maxExclusive": true, "default": 0.0, "description": "How much of the previous step carries over into the next one." } | |
| ] | |
| }, | |
| { | |
| "id": "nesterov", | |
| "label": "Nesterov momentum", | |
| "params": [ | |
| { "name": "learning_rate", "label": "Learning rate η", "symbol": "η", "kind": "number", "min": 0, "minExclusive": true, "default": 0.1, "description": "How far each step moves along the negative gradient." }, | |
| { "name": "momentum", "label": "Momentum μ", "symbol": "μ", "kind": "number", "min": 0, "max": 1, "maxExclusive": true, "default": 0.1, "description": "How much of the previous step carries over; the gradient is taken at the look-ahead point." } | |
| ] | |
| }, | |
| { | |
| "id": "newton", | |
| "label": "Newton's method", | |
| "params": [] | |
| }, | |
| { | |
| "id": "adam", | |
| "label": "Adam", | |
| "params": [ | |
| { "name": "learning_rate", "label": "Learning rate η", "symbol": "η", "kind": "number", "min": 0, "minExclusive": true, "default": 0.1, "description": "The largest step size, roughly." }, | |
| { "name": "beta1", "label": "Decay β₁", "symbol": "β₁", "kind": "number", "min": 0, "max": 1, "maxExclusive": true, "default": 0.9, "description": "Decay rate of the moving average of gradients (first moment)." }, | |
| { "name": "beta2", "label": "Decay β₂", "symbol": "β₂", "kind": "number", "min": 0, "max": 1, "maxExclusive": true, "default": 0.999, "description": "Decay rate of the moving average of squared gradients (second moment)." }, | |
| { "name": "epsilon", "label": "Epsilon ε", "symbol": "ε", "kind": "number", "min": 0, "minExclusive": true, "default": 1e-8, "description": "Added to the denominator to avoid dividing by zero." } | |
| ] | |
| }, | |
| { | |
| "id": "adagrad", | |
| "label": "Adagrad", | |
| "params": [ | |
| { "name": "learning_rate", "label": "Learning rate η", "symbol": "η", "kind": "number", "min": 0, "minExclusive": true, "default": 0.1, "description": "Divided by the root of the summed squared gradients." }, | |
| { "name": "epsilon", "label": "Epsilon ε", "symbol": "ε", "kind": "number", "min": 0, "minExclusive": true, "default": 1e-8, "description": "Added to the denominator to avoid dividing by zero." } | |
| ] | |
| }, | |
| { | |
| "id": "rmsprop", | |
| "label": "RMSProp", | |
| "params": [ | |
| { "name": "learning_rate", "label": "Learning rate η", "symbol": "η", "kind": "number", "min": 0, "minExclusive": true, "default": 0.1, "description": "Divided by the root of the moving average of squared gradients." }, | |
| { "name": "beta", "label": "Decay β", "symbol": "β", "kind": "number", "min": 0, "max": 1, "maxExclusive": true, "default": 0.9, "description": "Decay rate of the moving average of squared gradients." }, | |
| { "name": "epsilon", "label": "Epsilon ε", "symbol": "ε", "kind": "number", "min": 0, "minExclusive": true, "default": 1e-8, "description": "Added to the denominator to avoid dividing by zero." } | |
| ] | |
| }, | |
| { | |
| "id": "adadelta", | |
| "label": "Adadelta", | |
| "params": [ | |
| { "name": "beta", "label": "Decay β", "symbol": "β", "kind": "number", "min": 0, "max": 1, "maxExclusive": true, "default": 0.9, "description": "Decay rate of the moving averages of squared gradients and squared updates." }, | |
| { "name": "epsilon", "label": "Epsilon ε", "symbol": "ε", "kind": "number", "min": 0, "minExclusive": true, "default": 0.001, "description": "Sets the first step size, and avoids dividing by zero." } | |
| ] | |
| } | |
| ] | |
| } | |