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0_511_513.mp3
越 接 近 越 好
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0_513_513.mp3
所 以 我 們 呢
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0_513_518.mp3
把 θi 跟 θ 上 標 b 下 標 i 相 減
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69.444358
69.556786
0.994045
0.994063
0_518_519.mp3
然 後 取 它 們 的 平 方
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67.140794
67.669297
0.95259
0.949757
0_520_521.mp3
那 我 們 在 前 面 呢
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68.960186
69.46339
0.992748
0.992759
0_521_524.mp3
會 乘 上 一 個 數 值 叫 做 bi
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0_524_526.mp3
這 個 bi 就 是 要 告 訴 我 們 說
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70.721196
70.880063
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0_526_529.mp3
到 底 我 們 有 多 強 烈 地 希 望
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θi 跟 θ 上 標 b 下 標 i
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0_533_534.mp3
越 靠 近 越 好
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0_534_536.mp3
如 果 bi 的 值 很 大
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0_536_539.mp3
就 代 表 說 我 們 希 望 θi 跟 θbi 非 常 靠 近
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0_541_545.mp3
代 表 我 們 覺 得 θi 沒 有 跟 θbi 很 靠 近
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64.88978
65.813791
0.96396
0.967643
0_545_546.mp3
也 無 所 謂
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68.479065
68.95929
0.978562
0.978562
0_547_548.mp3
好 那 這 個 呢
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66.845605
66.971714
0.895418
0.898481
0_548_550.mp3
就 是 我 們 要 optimize
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71.084754
71.184167
0.911297
0.908236
0_550_551.mp3
這 個 l' 呢
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69.170138
69.232362
0.909517
0.93694
0_551_553.mp3
就 是 我 們 真 正 要 optimize 的 對 象
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69.056541
69.069465
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0_553_555.mp3
它 裡 面 有 兩 項
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60.372206
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0_555_557.mp3
一 個 是 原 來 的 新 的 任 務 的 loss
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66.598665
66.849946
0.984264
0.985222
0_557_558.mp3
另 外 一 項 呢
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70.146218
70.743914
0.994028
0.994028
0_558_562.mp3
就 是 要 讓 θi 跟 θbi 越 接 近 越 好
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但 是 要 注 意 一 下
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0_564_565.mp3
我 們 並 不 是
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0_566_568.mp3
平 等 地 去 看 待
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69.345483
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0_568_571.mp3
所 有 的 參 數 要 不 要 接 近 這 件 事
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68.616553
69.21947
0.974221
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0_571_575.mp3
我 們 其 實 只 要 求 θ 跟 θbi
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70.928797
71.171481
0.983882
0.983883
0_575_577.mp3
在 某 些 參 數 上 接 近 就 好
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0_577_580.mp3
並 不 需 要 所 有 參 數 都 接 近
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69.947352
70.613508
0.977953
0.977953
0_580_582.mp3
只 要 某 些 參 數 接 近 就 好
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68.609485
68.869824
0.99072
0.990723
0_582_584.mp3
那 哪 些 參 數 要 接 近
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69.568029
70.088136
0.961501
0.961789
0_584_586.mp3
就 由 bi 來 控 制
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69.613641
69.904001
0.966517
0.966517
0_586_587.mp3
如 果 某 一 個 參 數 i
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69.710652
69.774805
0.904389
0.904636
0_587_589.mp3
第 i 個 參 數 它 的 bi 很 大
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65.779365
65.857648
0.981176
0.986133
0_589_591.mp3
就 代 表 我 們 希 望 第 i 個 參 數
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0_591_593.mp3
它 跟 舊 的 參 數
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0_593_594.mp3
之 前 的 任 務 learn 出 來 的 那 個 參 數
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69.623589
70.530021
0.914252
0.916254
0_594_595.mp3
要 非 常 接 近
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71.418212
71.742291
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0_595_597.mp3
反 之 bi 等 於 0 就 代 表
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70.361048
70.39978
0.968137
0.968636
0_597_599.mp3
我 們 根 本 不 care 新 的 參 數 跟 舊 的 參 數
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68.913292
69.629279
0.953402
0.953053
0_599_601.mp3
到 底 要 不 要 接 近
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69.991658
71.211214
0.999134
0.999134
0_602_604.mp3
好 所 以 如 果 今 天 呢
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bi 設 為 0
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那 意 味 著 什 麼
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70.507341
71.042158
0.975714
0.975714
0_611_612.mp3
那 意 味 著 就 是
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69.968597
70.345826
0.993063
0.993007
0_612_616.mp3
我 們 沒 有 給 我 們 的 θi 任 何 限 制
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0_616_619.mp3
我 們 完 全 沒 有 要 求 新 的 learn 出 來 的 參 數
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跟 過 去 學 出 來 的 參 數 有 什 麼 樣 的 關 係
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69.440097
69.653603
0.994413
0.994414
0_623_625.mp3
那 這 個 時 候 就 是 一 般 的 training
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67.374357
67.518605
0.984283
0.984477
0_625_628.mp3
就 會 有 catastrophic forgetting 的 問 題
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64.79052
65.336409
0.99486
0.994804
0_628_631.mp3
但 是 你 可 能 會 想 說 既 然 bi 設 0 是 不 好 的
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70.391236
70.391236
0.964259
0.967993
0_631_634.mp3
那 我 們 就 把 bi 給 它 設 一 個 非 常 大 的 值
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0_636_639.mp3
所 有 的 參 數 都 給 它 一 個 非 常 大 的 bi
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61.756299
61.775758
0.876985
0.872404
0_639_641.mp3
那 這 樣 就 不 會 有 forgetting 的 問 題
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66.994904
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0_641_643.mp3
但 是 你 會 進 入 另 外 一 個 極 端
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0_643_646.mp3
這 個 極 端 叫 做 intransigence
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69.364968
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0_646_648.mp3
這 個 極 這 個 intransigence 的 意 思 就 是
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0_648_651.mp3
這 個 不 肯 妥 協 不 肯 讓 步
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58.863992
58.766794
0.981737
0.982052
0_651_653.mp3
頑 固 的 意 思
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65.610301
66.789701
0.975607
0.975607
0_653_656.mp3
所 以 intransigence 的 意 思 是 說
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0_656_658.mp3
假 設 你 現 在 bi 非 常 地
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0_658_659.mp3
非 常 地 大
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68.367109
68.788281
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0_659_661.mp3
那 你 最 後 learn 出 來 的 結 果
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70.256199
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0_661_664.mp3
θi 跟 θb 就 會 非 常 地 接 近
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64.557617
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0_664_667.mp3
你 的 新 的 參 數 跟 舊 的 參 數 會 非 常 接 近
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68.265067
69.294188
0.990561
0.990614
0_667_668.mp3
那 你 的 模 型
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69.891686
70.597814
0.987814
0.987814
0_668_670.mp3
可 能 在 舊 的 任 務 上 不 會 遺 忘
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68.651161
69.199898
0.947329
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0_670_672.mp3
但 新 的 任 務 它 學 不 好
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69.344463
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0_672_674.mp3
它 沒 有 能 力 去 把 新 的 任 務 學 好
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0_674_677.mp3
那 這 種 狀 況 就 叫 做 intransigence
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61.319174
61.560369
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0.9878
0_678_679.mp3
好 講 到 這 邊
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70.114342
70.114342
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0_679_681.mp3
我 們 來 看 一 下 有 沒 有 同 學 有 問 題 要 問 的
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好 有 同 學 說
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聲 音 還 是 炸
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希 望 現 在 有 好 很 多
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現 在 希 望 現 在 有 好 很 多
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57.294957
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0_698_700.mp3
好 有 同 學 問 說
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bi 是 要 人 為 設 定
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0_703_709.mp3
還 是 可 以 作 為 參 數 的 一 部 分 給 機 器 訓 練
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68.605962
69.336399
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0_709_711.mp3
好 那 再 等 一 下
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69.84296
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0_711_712.mp3
在 文 獻 上
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這 個 bi 都 是 人 為 設 定 的
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0_716_718.mp3
在 lifelong learning 的 研 究 裡 面
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關 鍵 的 技 術 就 在 於
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0_720_723.mp3
我 們 怎 麼 設 定 這 個 bi
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0_723_726.mp3
那 如 果 bi 用 learn 的 到 底 行 不 行 呢
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67.53177
68.173436
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0_726_728.mp3
你 可 以 想 見 說 在 這 個 任 務 裡 面
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0_728_731.mp3
你 恐 怕 不 能 讓 bi 用 learn 的
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67.494515
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0_731_733.mp3
如 果 你 讓 bi 自 己 學
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0_733_734.mp3
它 會 學 出 什 麼
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69.252098
70.125369
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0_734_737.mp3
對 它 來 說 它 要 讓 loss 越 小 越 好 嘛
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65.351411
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0_737_738.mp3
那 怎 麼 讓 loss 最 小
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直 接 bi 等 於 0
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60.21995
60.484108
0.949509
0.952743
0_739_740.mp3
loss 就 最 小 了
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68.848726
68.965211
0.994254
0.994228
0_740_743.mp3
所 以 如 果 你 讓 bi 直 接 用 learn 的
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71.062118
71.259731
0.977029
0.978281
0_743_745.mp3
你 並 沒 有 辦 法 達 到 lifelong learning 的 效 果
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