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它 們 的 意 思 是 說
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61.309632
61.314927
33_1768_1771.mp3
當 你 的 模 型 先 學 完 任 務 一 的 時 候
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60.411315
60.363728
33_1771_1772.mp3
在 任 務 一 上 的 正 確 率
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43.972779
44.994014
33_1773_1776.mp3
跟 學 到 大 t 個 任 務 完 以 後
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55.928359
55.87945
33_1776_1778.mp3
在 任 務 一 上 的 正 確 率 差 多 少
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65.539191
65.828993
33_1778_1780.mp3
當 學 完 任 務 一 的 時 候 記 憶 猶 新
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67.090759
67.090759
33_1780_1782.mp3
這 個 時 候 正 確 率 是 最 高 的
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70.084959
70.220424
33_1782_1784.mp3
那 隨 著 學 的 任 務 越 來 越 多
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69.418166
69.418166
33_1784_1787.mp3
那 你 的 正 確 率 就 會 不 斷 地 遞 減
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66.13832
66.190755
33_1788_1790.mp3
那 到 底 會 減 少 多 少 呢
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69.331342
69.744266
33_1790_1792.mp3
所 以 我 們 把 這 兩 個 r 進 行 相 減
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70.812532
70.981074
33_1792_1795.mp3
可 以 評 估 說 現 在 遺 忘 的 程 度 有 多 嚴 重
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69.502825
69.580292
33_1796_1799.mp3
那 因 為 呢 機 器 每 次 看 到 新 的 任 務 以 後
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69.312423
69.320226
33_1799_1800.mp3
舊 的 任 務 就 會 不 斷 遺 忘
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65.358544
65.350555
33_1800_1801.mp3
所 以 你 可 以 想 見 說
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32.789334
30.918422
33_1801_1804.mp3
rt 1 通 常 是 比 r1 1 小 的 了
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50.967839
50.925357
33_1804_1806.mp3
rt 2 通 常 是 比 r2 2 小 的 了
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67.585711
67.641273
33_1806_1809.mp3
所 以 如 果 你 是 拿 rt 1 減 r1 1
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47.582183
47.573712
33_1809_1811.mp3
rt 2 減 r2 2 的 話
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64.377472
64.418637
33_1811_1813.mp3
你 通 常 得 到 的 值 是 負 的
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70.019111
70.082999
33_1813_1814.mp3
所 以 backward transfer
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70.388156
70.388156
33_1814_1818.mp3
通 常 算 出 來 的 值 是 負 的 是 小 於 0 的
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67.507351
67.67337
33_1818_1820.mp3
如 果 你 今 天 可 以 提 出 一 個
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61.701805
61.704971
33_1820_1821.mp3
life long learning 的 方 法
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65.794873
65.85007
33_1821_1822.mp3
它 很 厲 害
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69.593205
69.755473
33_1822_1824.mp3
它 的 backward transfer 算 出 來 是 正 的
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70.395288
70.395288
33_1824_1825.mp3
那 你 就 很 厲 害 了
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67.726886
67.744045
33_1825_1828.mp3
因 為 通 常 backward transfer 都 是 負 的
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67.690797
67.778651
33_1828_1829.mp3
如 果 你 說
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66.966828
67.073194
33_1829_1830.mp3
機 器 學 了 新 的 任 務 以 後
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68.358353
68.364691
33_1830_1832.mp3
它 還 可 以 觸 類 旁 通
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69.29386
69.583502
33_1832_1834.mp3
把 原 來 的 任 務 一 做 得 更 好
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17.384818
17.408444
33_1834_1836.mp3
它 學 完 新 的 任 務 以 後 觸 類 旁 通
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69.036251
69.036931
33_1836_1837.mp3
把 原 來 的 任 務 二 做 得 更 好
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62.020955
62.192935
33_1838_1840.mp3
你 提 出 來 的 life long learning 就 很 厲 害 了
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67.719679
67.76933
33_1840_1842.mp3
一 般 life long learning 做 不 到 這 件 事
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51.647504
52.108576
33_1842_1844.mp3
通 常 只 要 這 個 值 不 要 負 得 太 嚴 重
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69.920662
69.97164
33_1844_1845.mp3
就 已 經 很 厲 害 了
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68.718503
68.871363
33_1847_1848.mp3
好 那 還 有 一 種 評 估 方 式
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16.336961
16.160836
33_1848_1851.mp3
叫 做 forward transfer
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57.791889
58.183032
33_1851_1852.mp3
那 forward transfer
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69.978099
69.978099
33_1852_1854.mp3
通 常 就 比 較 不 是 life long learning 的 重 點
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64.866859
64.988413
33_1854_1856.mp3
forward transfer 想 要 問 的 問 題 是 說
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63.982272
63.982272
33_1856_1860.mp3
今 天 在 看 過 一 系 列 的 任 務
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66.100115
66.260521
33_1860_1862.mp3
我 這 個 有 點 卡 頓
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68.045071
68.043755
33_1862_1863.mp3
我 也 不 知 道 為 什 麼
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59.915064
58.541981
33_1863_1865.mp3
我 的 那 個 滑 鼠 有 點 卡 頓
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69.012591
69.196171
33_1866_1867.mp3
好 不 過 沒 關 係
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62.571445
62.571445
33_1867_1868.mp3
我 們 現 在 看 看 同 學 有 沒 有 問 題
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66.899763
67.039896
33_1868_1869.mp3
好 大 家 沒 有 問 題
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67.206186
67.129601
33_1869_1870.mp3
好 我 們 繼 續 講
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68.704748
68.704748
33_1872_1873.mp3
好 今 天 這 個 forward transfer
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51.203282
51.019942
33_1873_1875.mp3
要 問 的 問 題 是 說 呢
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67.992358
68.063079
33_1875_1877.mp3
在 還 沒 有 看 過 某 個 任 務
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66.466704
66.521456
33_1877_1880.mp3
只 看 過 其 他 任 務 的 時 候
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67.698892
68.356698
33_1880_1882.mp3
機 器 到 底 已 經 學 到 什 麼 樣 的 程 度
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70.235859
70.546404
33_1883_1885.mp3
所 以 你 在 做 forward transfer 的 時 候
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44.892356
44.848985
33_1885_1890.mp3
你 就 是 拿 rt 1 t 去 減 r0 t
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70.089802
70.250544
33_1891_1895.mp3
這 個 rt 1 t 去 減 r0 t
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66.608119
66.684055
33_1895_1896.mp3
到 底 意 思 呢
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67.125374
67.19012
33_1896_1897.mp3
它 的 意 思 是 說
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47.190542
47.272161
33_1897_1899.mp3
今 天 在 還 沒 有 看 到 任 務 大 t 的 時 候
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56.556454
56.713465
33_1899_1903.mp3
只 看 到 任 務 t1 到 t 1
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70.634086
70.686659
33_1903_1906.mp3
只 看 到 任 務 t1 到 t 1 的 時 候
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66.083571
66.10926
33_1906_1910.mp3
你 的 模 型 到 底 可 以 學 出 什 麼 樣 程 度 的 結 果
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66.809003
66.978193
33_1910_1912.mp3
這 個 是 forward transfer
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69.344901
69.49526
33_1914_1916.mp3
好 那 接 下 來 就 是 準 備 要 進 入
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68.925059
69.069373
33_1916_1918.mp3
這 個 life long learning 的 解 法
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